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What is a Literature Review? How to Write It (with Examples)

A literature review is a critical analysis and synthesis of existing research on a particular topic. It provides an overview of the current state of knowledge, identifies gaps, and highlights key findings in the literature. 1 The purpose of a literature review is to situate your own research within the context of existing scholarship, demonstrating your understanding of the topic and showing how your work contributes to the ongoing conversation in the field. Learning how to write a literature review is a critical tool for successful research. Your ability to summarize and synthesize prior research pertaining to a certain topic demonstrates your grasp on the topic of study, and assists in the learning process. 

Table of Contents

• What is the purpose of literature review? 
• a. Habitat Loss and Species Extinction: 
• b. Range Shifts and Phenological Changes: 
• c. Ocean Acidification and Coral Reefs: 
• d. Adaptive Strategies and Conservation Efforts: 

How to write a good literature review 

• Choose a Topic and Define the Research Question: 
• Decide on the Scope of Your Review: 
• Select Databases for Searches: 
• Conduct Searches and Keep Track: 
• Review the Literature: 
• Organize and Write Your Literature Review: 
• How to write a literature review faster with Paperpal? 
• Frequently asked questions 

What is a literature review?

A well-conducted literature review demonstrates the researcher’s familiarity with the existing literature, establishes the context for their own research, and contributes to scholarly conversations on the topic. One of the purposes of a literature review is also to help researchers avoid duplicating previous work and ensure that their research is informed by and builds upon the existing body of knowledge.

What is the purpose of literature review?

A literature review serves several important purposes within academic and research contexts. Here are some key objectives and functions of a literature review: 2  

1. Contextualizing the Research Problem: The literature review provides a background and context for the research problem under investigation. It helps to situate the study within the existing body of knowledge. 

2. Identifying Gaps in Knowledge: By identifying gaps, contradictions, or areas requiring further research, the researcher can shape the research question and justify the significance of the study. This is crucial for ensuring that the new research contributes something novel to the field. 

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3. Understanding Theoretical and Conceptual Frameworks: Literature reviews help researchers gain an understanding of the theoretical and conceptual frameworks used in previous studies. This aids in the development of a theoretical framework for the current research. 

4. Providing Methodological Insights: Another purpose of literature reviews is that it allows researchers to learn about the methodologies employed in previous studies. This can help in choosing appropriate research methods for the current study and avoiding pitfalls that others may have encountered. 

5. Establishing Credibility: A well-conducted literature review demonstrates the researcher’s familiarity with existing scholarship, establishing their credibility and expertise in the field. It also helps in building a solid foundation for the new research. 

6. Informing Hypotheses or Research Questions: The literature review guides the formulation of hypotheses or research questions by highlighting relevant findings and areas of uncertainty in existing literature. 

Literature review example

Let’s delve deeper with a literature review example: Let’s say your literature review is about the impact of climate change on biodiversity. You might format your literature review into sections such as the effects of climate change on habitat loss and species extinction, phenological changes, and marine biodiversity. Each section would then summarize and analyze relevant studies in those areas, highlighting key findings and identifying gaps in the research. The review would conclude by emphasizing the need for further research on specific aspects of the relationship between climate change and biodiversity. The following literature review template provides a glimpse into the recommended literature review structure and content, demonstrating how research findings are organized around specific themes within a broader topic. 

Literature Review on Climate Change Impacts on Biodiversity:

Climate change is a global phenomenon with far-reaching consequences, including significant impacts on biodiversity. This literature review synthesizes key findings from various studies: 

a. Habitat Loss and Species Extinction:

Climate change-induced alterations in temperature and precipitation patterns contribute to habitat loss, affecting numerous species (Thomas et al., 2004). The review discusses how these changes increase the risk of extinction, particularly for species with specific habitat requirements. 

b. Range Shifts and Phenological Changes:

Observations of range shifts and changes in the timing of biological events (phenology) are documented in response to changing climatic conditions (Parmesan & Yohe, 2003). These shifts affect ecosystems and may lead to mismatches between species and their resources. 

c. Ocean Acidification and Coral Reefs:

The review explores the impact of climate change on marine biodiversity, emphasizing ocean acidification’s threat to coral reefs (Hoegh-Guldberg et al., 2007). Changes in pH levels negatively affect coral calcification, disrupting the delicate balance of marine ecosystems. 

d. Adaptive Strategies and Conservation Efforts:

Recognizing the urgency of the situation, the literature review discusses various adaptive strategies adopted by species and conservation efforts aimed at mitigating the impacts of climate change on biodiversity (Hannah et al., 2007). It emphasizes the importance of interdisciplinary approaches for effective conservation planning. 

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Writing a literature review involves summarizing and synthesizing existing research on a particular topic. A good literature review format should include the following elements. 

Introduction: The introduction sets the stage for your literature review, providing context and introducing the main focus of your review. 

• Opening Statement: Begin with a general statement about the broader topic and its significance in the field. 
• Scope and Purpose: Clearly define the scope of your literature review. Explain the specific research question or objective you aim to address. 
• Organizational Framework: Briefly outline the structure of your literature review, indicating how you will categorize and discuss the existing research. 
• Significance of the Study: Highlight why your literature review is important and how it contributes to the understanding of the chosen topic. 
• Thesis Statement: Conclude the introduction with a concise thesis statement that outlines the main argument or perspective you will develop in the body of the literature review. 

Body: The body of the literature review is where you provide a comprehensive analysis of existing literature, grouping studies based on themes, methodologies, or other relevant criteria. 

• Organize by Theme or Concept: Group studies that share common themes, concepts, or methodologies. Discuss each theme or concept in detail, summarizing key findings and identifying gaps or areas of disagreement. 
• Critical Analysis: Evaluate the strengths and weaknesses of each study. Discuss the methodologies used, the quality of evidence, and the overall contribution of each work to the understanding of the topic. 
• Synthesis of Findings: Synthesize the information from different studies to highlight trends, patterns, or areas of consensus in the literature. 
• Identification of Gaps: Discuss any gaps or limitations in the existing research and explain how your review contributes to filling these gaps. 
• Transition between Sections: Provide smooth transitions between different themes or concepts to maintain the flow of your literature review. 

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Conclusion: The conclusion of your literature review should summarize the main findings, highlight the contributions of the review, and suggest avenues for future research. 

• Summary of Key Findings: Recap the main findings from the literature and restate how they contribute to your research question or objective. 
• Contributions to the Field: Discuss the overall contribution of your literature review to the existing knowledge in the field. 
• Implications and Applications: Explore the practical implications of the findings and suggest how they might impact future research or practice. 
• Recommendations for Future Research: Identify areas that require further investigation and propose potential directions for future research in the field. 
• Final Thoughts: Conclude with a final reflection on the importance of your literature review and its relevance to the broader academic community. 

Conducting a literature review

Conducting a literature review is an essential step in research that involves reviewing and analyzing existing literature on a specific topic. It’s important to know how to do a literature review effectively, so here are the steps to follow: 1  

Choose a Topic and Define the Research Question:

• Select a topic that is relevant to your field of study. 
• Clearly define your research question or objective. Determine what specific aspect of the topic do you want to explore? 

Decide on the Scope of Your Review:

• Determine the timeframe for your literature review. Are you focusing on recent developments, or do you want a historical overview? 
• Consider the geographical scope. Is your review global, or are you focusing on a specific region? 
• Define the inclusion and exclusion criteria. What types of sources will you include? Are there specific types of studies or publications you will exclude? 

Select Databases for Searches:

• Identify relevant databases for your field. Examples include PubMed, IEEE Xplore, Scopus, Web of Science, and Google Scholar. 
• Consider searching in library catalogs, institutional repositories, and specialized databases related to your topic. 

Conduct Searches and Keep Track:

• Develop a systematic search strategy using keywords, Boolean operators (AND, OR, NOT), and other search techniques. 
• Record and document your search strategy for transparency and replicability. 
• Keep track of the articles, including publication details, abstracts, and links. Use citation management tools like EndNote, Zotero, or Mendeley to organize your references. 

Review the Literature:

• Evaluate the relevance and quality of each source. Consider the methodology, sample size, and results of studies. 
• Organize the literature by themes or key concepts. Identify patterns, trends, and gaps in the existing research. 
• Summarize key findings and arguments from each source. Compare and contrast different perspectives. 
• Identify areas where there is a consensus in the literature and where there are conflicting opinions. 
• Provide critical analysis and synthesis of the literature. What are the strengths and weaknesses of existing research? 

Organize and Write Your Literature Review:

• Literature review outline should be based on themes, chronological order, or methodological approaches. 
• Write a clear and coherent narrative that synthesizes the information gathered. 
• Use proper citations for each source and ensure consistency in your citation style (APA, MLA, Chicago, etc.). 
• Conclude your literature review by summarizing key findings, identifying gaps, and suggesting areas for future research. 

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How to write a literature review faster with Paperpal?

Paperpal, an AI writing assistant, integrates powerful academic search capabilities within its writing platform. With the Research feature, you get 100% factual insights, with citations backed by 250M+ verified research articles, directly within your writing interface with the option to save relevant references in your Citation Library. By eliminating the need to switch tabs to find answers to all your research questions, Paperpal saves time and helps you stay focused on your writing.   

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• Cite with Confidence: Paperpal makes it easy to incorporate relevant citations and references into your writing, ensuring your arguments are well-supported by credible sources. This translates to a polished, well-researched literature review. 

The literature review sample and detailed advice on writing and conducting a review will help you produce a well-structured report. But remember that a good literature review is an ongoing process, and it may be necessary to revisit and update it as your research progresses. By combining effortless research with an easy citation process, Paperpal Research streamlines the literature review process and empowers you to write faster and with more confidence. Try Paperpal Research now and see for yourself.  

Frequently asked questions

A literature review is a critical and comprehensive analysis of existing literature (published and unpublished works) on a specific topic or research question and provides a synthesis of the current state of knowledge in a particular field. A well-conducted literature review is crucial for researchers to build upon existing knowledge, avoid duplication of efforts, and contribute to the advancement of their field. It also helps researchers situate their work within a broader context and facilitates the development of a sound theoretical and conceptual framework for their studies.

Literature review is a crucial component of research writing, providing a solid background for a research paper’s investigation. The aim is to keep professionals up to date by providing an understanding of ongoing developments within a specific field, including research methods, and experimental techniques used in that field, and present that knowledge in the form of a written report. Also, the depth and breadth of the literature review emphasizes the credibility of the scholar in his or her field.  

Before writing a literature review, it’s essential to undertake several preparatory steps to ensure that your review is well-researched, organized, and focused. This includes choosing a topic of general interest to you and doing exploratory research on that topic, writing an annotated bibliography, and noting major points, especially those that relate to the position you have taken on the topic. 

Literature reviews and academic research papers are essential components of scholarly work but serve different purposes within the academic realm. 3 A literature review aims to provide a foundation for understanding the current state of research on a particular topic, identify gaps or controversies, and lay the groundwork for future research. Therefore, it draws heavily from existing academic sources, including books, journal articles, and other scholarly publications. In contrast, an academic research paper aims to present new knowledge, contribute to the academic discourse, and advance the understanding of a specific research question. Therefore, it involves a mix of existing literature (in the introduction and literature review sections) and original data or findings obtained through research methods. 

Literature reviews are essential components of academic and research papers, and various strategies can be employed to conduct them effectively. If you want to know how to write a literature review for a research paper, here are four common approaches that are often used by researchers.  Chronological Review: This strategy involves organizing the literature based on the chronological order of publication. It helps to trace the development of a topic over time, showing how ideas, theories, and research have evolved.  Thematic Review: Thematic reviews focus on identifying and analyzing themes or topics that cut across different studies. Instead of organizing the literature chronologically, it is grouped by key themes or concepts, allowing for a comprehensive exploration of various aspects of the topic.  Methodological Review: This strategy involves organizing the literature based on the research methods employed in different studies. It helps to highlight the strengths and weaknesses of various methodologies and allows the reader to evaluate the reliability and validity of the research findings.  Theoretical Review: A theoretical review examines the literature based on the theoretical frameworks used in different studies. This approach helps to identify the key theories that have been applied to the topic and assess their contributions to the understanding of the subject.  It’s important to note that these strategies are not mutually exclusive, and a literature review may combine elements of more than one approach. The choice of strategy depends on the research question, the nature of the literature available, and the goals of the review. Additionally, other strategies, such as integrative reviews or systematic reviews, may be employed depending on the specific requirements of the research.

The literature review format can vary depending on the specific publication guidelines. However, there are some common elements and structures that are often followed. Here is a general guideline for the format of a literature review:  Introduction:   Provide an overview of the topic.  Define the scope and purpose of the literature review.  State the research question or objective.  Body:   Organize the literature by themes, concepts, or chronology.  Critically analyze and evaluate each source.  Discuss the strengths and weaknesses of the studies.  Highlight any methodological limitations or biases.  Identify patterns, connections, or contradictions in the existing research.  Conclusion:   Summarize the key points discussed in the literature review.  Highlight the research gap.  Address the research question or objective stated in the introduction.  Highlight the contributions of the review and suggest directions for future research.

Both annotated bibliographies and literature reviews involve the examination of scholarly sources. While annotated bibliographies focus on individual sources with brief annotations, literature reviews provide a more in-depth, integrated, and comprehensive analysis of existing literature on a specific topic. The key differences are as follows: 

References 

• Denney, A. S., & Tewksbury, R. (2013). How to write a literature review.  Journal of criminal justice education ,  24 (2), 218-234. 
• Pan, M. L. (2016).  Preparing literature reviews: Qualitative and quantitative approaches . Taylor & Francis. 
• Cantero, C. (2019). How to write a literature review.  San José State University Writing Center . 

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• UConn Library
• Literature Review: The What, Why and How-to Guide
• Introduction

Literature Review: The What, Why and How-to Guide — Introduction

• Getting Started
• How to Pick a Topic
• Strategies to Find Sources
• Evaluating Sources & Lit. Reviews
• Tips for Writing Literature Reviews
• Writing Literature Review: Useful Sites
• Citation Resources
• Other Academic Writings

What are Literature Reviews?

So, what is a literature review? "A literature review is an account of what has been published on a topic by accredited scholars and researchers. In writing the literature review, your purpose is to convey to your reader what knowledge and ideas have been established on a topic, and what their strengths and weaknesses are. As a piece of writing, the literature review must be defined by a guiding concept (e.g., your research objective, the problem or issue you are discussing, or your argumentative thesis). It is not just a descriptive list of the material available, or a set of summaries." Taylor, D.  The literature review: A few tips on conducting it . University of Toronto Health Sciences Writing Centre.

Goals of Literature Reviews

What are the goals of creating a Literature Review?  A literature could be written to accomplish different aims:

• To develop a theory or evaluate an existing theory
• To summarize the historical or existing state of a research topic
• Identify a problem in a field of research 

Baumeister, R. F., & Leary, M. R. (1997). Writing narrative literature reviews .  Review of General Psychology , 1 (3), 311-320.

What kinds of sources require a Literature Review?

• A research paper assigned in a course
• A thesis or dissertation
• A grant proposal
• An article intended for publication in a journal

All these instances require you to collect what has been written about your research topic so that you can demonstrate how your own research sheds new light on the topic.

Types of Literature Reviews

What kinds of literature reviews are written?

Narrative review: The purpose of this type of review is to describe the current state of the research on a specific topic/research and to offer a critical analysis of the literature reviewed. Studies are grouped by research/theoretical categories, and themes and trends, strengths and weakness, and gaps are identified. The review ends with a conclusion section which summarizes the findings regarding the state of the research of the specific study, the gaps identify and if applicable, explains how the author's research will address gaps identify in the review and expand the knowledge on the topic reviewed.

• Example : Predictors and Outcomes of U.S. Quality Maternity Leave: A Review and Conceptual Framework:  10.1177/08948453211037398  

Systematic review : "The authors of a systematic review use a specific procedure to search the research literature, select the studies to include in their review, and critically evaluate the studies they find." (p. 139). Nelson, L. K. (2013). Research in Communication Sciences and Disorders . Plural Publishing.

• Example : The effect of leave policies on increasing fertility: a systematic review:  10.1057/s41599-022-01270-w

Meta-analysis : "Meta-analysis is a method of reviewing research findings in a quantitative fashion by transforming the data from individual studies into what is called an effect size and then pooling and analyzing this information. The basic goal in meta-analysis is to explain why different outcomes have occurred in different studies." (p. 197). Roberts, M. C., & Ilardi, S. S. (2003). Handbook of Research Methods in Clinical Psychology . Blackwell Publishing.

• Example : Employment Instability and Fertility in Europe: A Meta-Analysis:  10.1215/00703370-9164737

Meta-synthesis : "Qualitative meta-synthesis is a type of qualitative study that uses as data the findings from other qualitative studies linked by the same or related topic." (p.312). Zimmer, L. (2006). Qualitative meta-synthesis: A question of dialoguing with texts .  Journal of Advanced Nursing , 53 (3), 311-318.

• Example : Women’s perspectives on career successes and barriers: A qualitative meta-synthesis:  10.1177/05390184221113735

Literature Reviews in the Health Sciences

• UConn Health subject guide on systematic reviews Explanation of the different review types used in health sciences literature as well as tools to help you find the right review type
• << Previous: Getting Started
• Next: How to Pick a Topic >>
• Last Updated: Sep 21, 2022 2:16 PM
• URL: https://guides.lib.uconn.edu/literaturereview

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• 04 December 2020
• Correction 09 December 2020

How to write a superb literature review

Andy Tay is a freelance writer based in Singapore.

You can also search for this author in PubMed   Google Scholar

Literature reviews are important resources for scientists. They provide historical context for a field while offering opinions on its future trajectory. Creating them can provide inspiration for one’s own research, as well as some practice in writing. But few scientists are trained in how to write a review — or in what constitutes an excellent one. Even picking the appropriate software to use can be an involved decision (see ‘Tools and techniques’). So Nature asked editors and working scientists with well-cited reviews for their tips.

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doi: https://doi.org/10.1038/d41586-020-03422-x

Interviews have been edited for length and clarity.

Updates & Corrections

Correction 09 December 2020 : An earlier version of the tables in this article included some incorrect details about the programs Zotero, Endnote and Manubot. These have now been corrected.

Hsing, I.-M., Xu, Y. & Zhao, W. Electroanalysis 19 , 755–768 (2007).

Article   Google Scholar  

Ledesma, H. A. et al. Nature Nanotechnol. 14 , 645–657 (2019).

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Brahlek, M., Koirala, N., Bansal, N. & Oh, S. Solid State Commun. 215–216 , 54–62 (2015).

Choi, Y. & Lee, S. Y. Nature Rev. Chem . https://doi.org/10.1038/s41570-020-00221-w (2020).

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A literature review is a document or section of a document that collects key sources on a topic and discusses those sources in conversation with each other (also called synthesis ). The lit review is an important genre in many disciplines, not just literature (i.e., the study of works of literature such as novels and plays). When we say “literature review” or refer to “the literature,” we are talking about the research ( scholarship ) in a given field. You will often see the terms “the research,” “the scholarship,” and “the literature” used mostly interchangeably.

Where, when, and why would I write a lit review?

There are a number of different situations where you might write a literature review, each with slightly different expectations; different disciplines, too, have field-specific expectations for what a literature review is and does. For instance, in the humanities, authors might include more overt argumentation and interpretation of source material in their literature reviews, whereas in the sciences, authors are more likely to report study designs and results in their literature reviews; these differences reflect these disciplines’ purposes and conventions in scholarship. You should always look at examples from your own discipline and talk to professors or mentors in your field to be sure you understand your discipline’s conventions, for literature reviews as well as for any other genre.

A literature review can be a part of a research paper or scholarly article, usually falling after the introduction and before the research methods sections. In these cases, the lit review just needs to cover scholarship that is important to the issue you are writing about; sometimes it will also cover key sources that informed your research methodology.

Lit reviews can also be standalone pieces, either as assignments in a class or as publications. In a class, a lit review may be assigned to help students familiarize themselves with a topic and with scholarship in their field, get an idea of the other researchers working on the topic they’re interested in, find gaps in existing research in order to propose new projects, and/or develop a theoretical framework and methodology for later research. As a publication, a lit review usually is meant to help make other scholars’ lives easier by collecting and summarizing, synthesizing, and analyzing existing research on a topic. This can be especially helpful for students or scholars getting into a new research area, or for directing an entire community of scholars toward questions that have not yet been answered.

What are the parts of a lit review?

Most lit reviews use a basic introduction-body-conclusion structure; if your lit review is part of a larger paper, the introduction and conclusion pieces may be just a few sentences while you focus most of your attention on the body. If your lit review is a standalone piece, the introduction and conclusion take up more space and give you a place to discuss your goals, research methods, and conclusions separately from where you discuss the literature itself.

Introduction:

• An introductory paragraph that explains what your working topic and thesis is
• A forecast of key topics or texts that will appear in the review
• Potentially, a description of how you found sources and how you analyzed them for inclusion and discussion in the review (more often found in published, standalone literature reviews than in lit review sections in an article or research paper)
• Summarize and synthesize: Give an overview of the main points of each source and combine them into a coherent whole
• Analyze and interpret: Don’t just paraphrase other researchers – add your own interpretations where possible, discussing the significance of findings in relation to the literature as a whole
• Critically Evaluate: Mention the strengths and weaknesses of your sources
• Write in well-structured paragraphs: Use transition words and topic sentence to draw connections, comparisons, and contrasts.

Conclusion:

• Summarize the key findings you have taken from the literature and emphasize their significance
• Connect it back to your primary research question

How should I organize my lit review?

Lit reviews can take many different organizational patterns depending on what you are trying to accomplish with the review. Here are some examples:

• Chronological : The simplest approach is to trace the development of the topic over time, which helps familiarize the audience with the topic (for instance if you are introducing something that is not commonly known in your field). If you choose this strategy, be careful to avoid simply listing and summarizing sources in order. Try to analyze the patterns, turning points, and key debates that have shaped the direction of the field. Give your interpretation of how and why certain developments occurred (as mentioned previously, this may not be appropriate in your discipline — check with a teacher or mentor if you’re unsure).
• Thematic : If you have found some recurring central themes that you will continue working with throughout your piece, you can organize your literature review into subsections that address different aspects of the topic. For example, if you are reviewing literature about women and religion, key themes can include the role of women in churches and the religious attitude towards women.
• Qualitative versus quantitative research
• Empirical versus theoretical scholarship
• Divide the research by sociological, historical, or cultural sources
• Theoretical : In many humanities articles, the literature review is the foundation for the theoretical framework. You can use it to discuss various theories, models, and definitions of key concepts. You can argue for the relevance of a specific theoretical approach or combine various theorical concepts to create a framework for your research.

What are some strategies or tips I can use while writing my lit review?

Any lit review is only as good as the research it discusses; make sure your sources are well-chosen and your research is thorough. Don’t be afraid to do more research if you discover a new thread as you’re writing. More info on the research process is available in our "Conducting Research" resources .

As you’re doing your research, create an annotated bibliography ( see our page on the this type of document ). Much of the information used in an annotated bibliography can be used also in a literature review, so you’ll be not only partially drafting your lit review as you research, but also developing your sense of the larger conversation going on among scholars, professionals, and any other stakeholders in your topic.

Usually you will need to synthesize research rather than just summarizing it. This means drawing connections between sources to create a picture of the scholarly conversation on a topic over time. Many student writers struggle to synthesize because they feel they don’t have anything to add to the scholars they are citing; here are some strategies to help you:

• It often helps to remember that the point of these kinds of syntheses is to show your readers how you understand your research, to help them read the rest of your paper.
• Writing teachers often say synthesis is like hosting a dinner party: imagine all your sources are together in a room, discussing your topic. What are they saying to each other?
• Look at the in-text citations in each paragraph. Are you citing just one source for each paragraph? This usually indicates summary only. When you have multiple sources cited in a paragraph, you are more likely to be synthesizing them (not always, but often
• Read more about synthesis here.

The most interesting literature reviews are often written as arguments (again, as mentioned at the beginning of the page, this is discipline-specific and doesn’t work for all situations). Often, the literature review is where you can establish your research as filling a particular gap or as relevant in a particular way. You have some chance to do this in your introduction in an article, but the literature review section gives a more extended opportunity to establish the conversation in the way you would like your readers to see it. You can choose the intellectual lineage you would like to be part of and whose definitions matter most to your thinking (mostly humanities-specific, but this goes for sciences as well). In addressing these points, you argue for your place in the conversation, which tends to make the lit review more compelling than a simple reporting of other sources.

How to write a good scientific review article

Affiliation.

• 1 The FEBS Journal Editorial Office, Cambridge, UK.
• PMID: 35792782
• DOI: 10.1111/febs.16565

Literature reviews are valuable resources for the scientific community. With research accelerating at an unprecedented speed in recent years and more and more original papers being published, review articles have become increasingly important as a means to keep up to date with developments in a particular area of research. A good review article provides readers with an in-depth understanding of a field and highlights key gaps and challenges to address with future research. Writing a review article also helps to expand the writer's knowledge of their specialist area and to develop their analytical and communication skills, amongst other benefits. Thus, the importance of building review-writing into a scientific career cannot be overstated. In this instalment of The FEBS Journal's Words of Advice series, I provide detailed guidance on planning and writing an informative and engaging literature review.

© 2022 Federation of European Biochemical Societies.

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Literature reviews, what is a literature review, learning more about how to do a literature review.

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A literature review is a review and synthesis of existing research on a topic or research question. A literature review is meant to analyze the scholarly literature, make connections across writings and identify strengths, weaknesses, trends, and missing conversations. A literature review should address different aspects of a topic as it relates to your research question. A literature review goes beyond a description or summary of the literature you have read. 

• Sage Research Methods Core Collection This link opens in a new window SAGE Research Methods supports research at all levels by providing material to guide users through every step of the research process. SAGE Research Methods is the ultimate methods library with more than 1000 books, reference works, journal articles, and instructional videos by world-leading academics from across the social sciences, including the largest collection of qualitative methods books available online from any scholarly publisher. – Publisher

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What is a Literature Review?

A literature or narrative review is a comprehensive review and analysis of the published literature on a specific topic or research question. The literature that is reviewed contains: books, articles, academic articles, conference proceedings, association papers, and dissertations. It contains the most pertinent studies and points to important past and current research and practices. It provides background and context, and shows how your research will contribute to the field. 

A literature review should: 

• Provide a comprehensive and updated review of the literature;
• Explain why this review has taken place;
• Articulate a position or hypothesis;
• Acknowledge and account for conflicting and corroborating points of view

From  S age Research Methods

Purpose of a Literature Review

A literature review can be written as an introduction to a study to:

• Demonstrate how a study fills a gap in research
• Compare a study with other research that's been done

Or it can be a separate work (a research article on its own) which:

• Organizes or describes a topic
• Describes variables within a particular issue/problem

Limitations of a Literature Review

Some of the limitations of a literature review are:

• It's a snapshot in time. Unlike other reviews, this one has beginning, a middle and an end. There may be future developments that could make your work less relevant.
• It may be too focused. Some niche studies may miss the bigger picture.
• It can be difficult to be comprehensive. There is no way to make sure all the literature on a topic was considered.
• It is easy to be biased if you stick to top tier journals. There may be other places where people are publishing exemplary research. Look to open access publications and conferences to reflect a more inclusive collection. Also, make sure to include opposing views (and not just supporting evidence).

Source: Grant, Maria J., and Andrew Booth. “A Typology of Reviews: An Analysis of 14 Review Types and Associated Methodologies.” Health Information & Libraries Journal, vol. 26, no. 2, June 2009, pp. 91–108. Wiley Online Library, doi:10.1111/j.1471-1842.2009.00848.x.

Meryl Brodsky : Communication and Information Studies

Hannah Chapman Tripp : Biology, Neuroscience

Carolyn Cunningham : Human Development & Family Sciences, Psychology, Sociology

Larayne Dallas : Engineering

Janelle Hedstrom : Special Education, Curriculum & Instruction, Ed Leadership & Policy ​

Susan Macicak : Linguistics

Imelda Vetter : Dell Medical School

For help in other subject areas, please see the guide to library specialists by subject .

Periodically, UT Libraries runs a workshop covering the basics and library support for literature reviews. While we try to offer these once per academic year, we find providing the recording to be helpful to community members who have missed the session. Following is the most recent recording of the workshop, Conducting a Literature Review. To view the recording, a UT login is required.

• October 26, 2022 recording
• Last Updated: Oct 26, 2022 2:49 PM
• URL: https://guides.lib.utexas.edu/literaturereviews

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Review Typologies

There are many types of evidence synthesis projects, including systematic reviews as well as others. The selection of review type is wholly dependent on the research question. Not all research questions are well-suited for systematic reviews.

• Review Typologies (from LITR-EX) This site explores different review methodologies such as, systematic, scoping, realist, narrative, state of the art, meta-ethnography, critical, and integrative reviews. The LITR-EX site has a health professions education focus, but the advice and information is widely applicable.

Review the table to peruse review types and associated methodologies. Librarians can also help your team determine which review type might be appropriate for your project. 

Reproduced from Grant, M. J. and Booth, A. (2009), A typology of reviews: an analysis of 14 review types and associated methodologies. Health Information & Libraries Journal, 26: 91-108.  doi:10.1111/j.1471-1842.2009.00848.x

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• Critical Reviews

How to Write an Article Review (With Examples)

Last Updated: April 24, 2024 Fact Checked

Preparing to Write Your Review

Writing the article review, sample article reviews, expert q&a.

This article was co-authored by Jake Adams . Jake Adams is an academic tutor and the owner of Simplifi EDU, a Santa Monica, California based online tutoring business offering learning resources and online tutors for academic subjects K-College, SAT & ACT prep, and college admissions applications. With over 14 years of professional tutoring experience, Jake is dedicated to providing his clients the very best online tutoring experience and access to a network of excellent undergraduate and graduate-level tutors from top colleges all over the nation. Jake holds a BS in International Business and Marketing from Pepperdine University. There are 12 references cited in this article, which can be found at the bottom of the page. This article has been fact-checked, ensuring the accuracy of any cited facts and confirming the authority of its sources. This article has been viewed 3,105,302 times.

An article review is both a summary and an evaluation of another writer's article. Teachers often assign article reviews to introduce students to the work of experts in the field. Experts also are often asked to review the work of other professionals. Understanding the main points and arguments of the article is essential for an accurate summation. Logical evaluation of the article's main theme, supporting arguments, and implications for further research is an important element of a review . Here are a few guidelines for writing an article review.

Education specialist Alexander Peterman recommends: "In the case of a review, your objective should be to reflect on the effectiveness of what has already been written, rather than writing to inform your audience about a subject."

Article Review 101

• Read the article very closely, and then take time to reflect on your evaluation. Consider whether the article effectively achieves what it set out to.
• Write out a full article review by completing your intro, summary, evaluation, and conclusion. Don't forget to add a title, too!
• Proofread your review for mistakes (like grammar and usage), while also cutting down on needless information.

• Article reviews present more than just an opinion. You will engage with the text to create a response to the scholarly writer's ideas. You will respond to and use ideas, theories, and research from your studies. Your critique of the article will be based on proof and your own thoughtful reasoning.
• An article review only responds to the author's research. It typically does not provide any new research. However, if you are correcting misleading or otherwise incorrect points, some new data may be presented.
• An article review both summarizes and evaluates the article.

• Summarize the article. Focus on the important points, claims, and information.
• Discuss the positive aspects of the article. Think about what the author does well, good points she makes, and insightful observations.
• Identify contradictions, gaps, and inconsistencies in the text. Determine if there is enough data or research included to support the author's claims. Find any unanswered questions left in the article.

• Make note of words or issues you don't understand and questions you have.
• Look up terms or concepts you are unfamiliar with, so you can fully understand the article. Read about concepts in-depth to make sure you understand their full context.

• Pay careful attention to the meaning of the article. Make sure you fully understand the article. The only way to write a good article review is to understand the article.

• With either method, make an outline of the main points made in the article and the supporting research or arguments. It is strictly a restatement of the main points of the article and does not include your opinions.
• After putting the article in your own words, decide which parts of the article you want to discuss in your review. You can focus on the theoretical approach, the content, the presentation or interpretation of evidence, or the style. You will always discuss the main issues of the article, but you can sometimes also focus on certain aspects. This comes in handy if you want to focus the review towards the content of a course.
• Review the summary outline to eliminate unnecessary items. Erase or cross out the less important arguments or supplemental information. Your revised summary can serve as the basis for the summary you provide at the beginning of your review.

• What does the article set out to do?
• What is the theoretical framework or assumptions?
• Are the central concepts clearly defined?
• How adequate is the evidence?
• How does the article fit into the literature and field?
• Does it advance the knowledge of the subject?
• How clear is the author's writing? Don't: include superficial opinions or your personal reaction. Do: pay attention to your biases, so you can overcome them.

• For example, in MLA , a citation may look like: Duvall, John N. "The (Super)Marketplace of Images: Television as Unmediated Mediation in DeLillo's White Noise ." Arizona Quarterly 50.3 (1994): 127-53. Print. [9] X Trustworthy Source Purdue Online Writing Lab Trusted resource for writing and citation guidelines Go to source

• For example: The article, "Condom use will increase the spread of AIDS," was written by Anthony Zimmerman, a Catholic priest.

• Your introduction should only be 10-25% of your review.
• End the introduction with your thesis. Your thesis should address the above issues. For example: Although the author has some good points, his article is biased and contains some misinterpretation of data from others’ analysis of the effectiveness of the condom.

• Use direct quotes from the author sparingly.
• Review the summary you have written. Read over your summary many times to ensure that your words are an accurate description of the author's article.

• Support your critique with evidence from the article or other texts.
• The summary portion is very important for your critique. You must make the author's argument clear in the summary section for your evaluation to make sense.
• Remember, this is not where you say if you liked the article or not. You are assessing the significance and relevance of the article.
• Use a topic sentence and supportive arguments for each opinion. For example, you might address a particular strength in the first sentence of the opinion section, followed by several sentences elaborating on the significance of the point.

• This should only be about 10% of your overall essay.
• For example: This critical review has evaluated the article "Condom use will increase the spread of AIDS" by Anthony Zimmerman. The arguments in the article show the presence of bias, prejudice, argumentative writing without supporting details, and misinformation. These points weaken the author’s arguments and reduce his credibility.

• Make sure you have identified and discussed the 3-4 key issues in the article.

You Might Also Like

• ↑ https://libguides.cmich.edu/writinghelp/articlereview
• ↑ https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4548566/
• ↑ Jake Adams. Academic Tutor & Test Prep Specialist. Expert Interview. 24 July 2020.
• ↑ https://guides.library.queensu.ca/introduction-research/writing/critical
• ↑ https://www.iup.edu/writingcenter/writing-resources/organization-and-structure/creating-an-outline.html
• ↑ https://writing.umn.edu/sws/assets/pdf/quicktips/titles.pdf
• ↑ https://owl.purdue.edu/owl/research_and_citation/mla_style/mla_formatting_and_style_guide/mla_works_cited_periodicals.html
• ↑ https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4548565/
• ↑ https://writingcenter.uconn.edu/wp-content/uploads/sites/593/2014/06/How_to_Summarize_a_Research_Article1.pdf
• ↑ https://www.uis.edu/learning-hub/writing-resources/handouts/learning-hub/how-to-review-a-journal-article
• ↑ https://writingcenter.unc.edu/tips-and-tools/editing-and-proofreading/

About This Article

If you have to write an article review, read through the original article closely, taking notes and highlighting important sections as you read. Next, rewrite the article in your own words, either in a long paragraph or as an outline. Open your article review by citing the article, then write an introduction which states the article’s thesis. Next, summarize the article, followed by your opinion about whether the article was clear, thorough, and useful. Finish with a paragraph that summarizes the main points of the article and your opinions. To learn more about what to include in your personal critique of the article, keep reading the article! Did this summary help you? Yes No

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AcademyHealth Presents a Literature Review Summarizing the Research Findings of the Use of Internet Search Data in the Diagnosis of Diseases and Conditions

Sponsored by a grant from the Gordon and Betty Moore Foundation, and in partnership with Innovation Horizons, AcademyHealth conducted a literature review on the use of patient-generated data to assess the capability of the internet as a tool to inform clinical diagnosis practices.

As a component of an ongoing research project to address the gaps in medical care that contribute to delayed or missed diagnosis of serious disease and conditions, AcademyHealth has engaged in a study to examine how the use of a patient’s internet search data can be applied as a data source and tool to inform clinical diagnosis practices. Sponsored by a grant from the Gordon and Betty Moore Foundation, a literature review and comparative analyses were conducted utilizing data from internet searches by patients; the purpose of the review and analyses was to identify correlations (or a lack thereof) between each patient's searches and the corresponding patient's medical diagnoses. While many scientific reviews have previously summarized the utility of population-level internet search data for public health and health outcomes research, this is the first documented assessment of peer-reviewed publications focused on personalized medical diagnostic use. AcademyHealth conducted this study to help guide health services researchers, patient advocates, health care policy makers, and others to learn more about these data resources and their potential to inform new approaches to address diagnostic gaps and opportunities. This approach applies patient-generated data to assess the capability of the internet as a tool to improve understanding of symptoms, illuminate warning signs leading to a medical diagnostic workup, and empower caregivers to more effectively respond to health concerns.

The study design and findings represented in this report were reviewed by an Academy Health multidisciplinary steering committee that approved the report. The report details how researchers obtained and analyzed patient data from Microsoft and Google search engines to then link the data with the corresponding patient’s clinical information. All patient-generated data was provided by patients retrospectively with informed consent for research use. Of the 43 peer-reviewed publications identified and reviewed by AcademyHealth for inclusion in the report, all were retrospective analyses. The analyses included in the report represented a variety of medical and health considerations including cancer, mental health conditions, vulnerability, violence, and personal safety associated with neurodegenerative and aging disorders. Also included in the report were features published by researchers about tools that were developed to enable large data sets to be analyzed and integrated with other data, such as clinical trials and clinical care data. Cumulatively, these publications provide unique insights into the patient information needs, informed consent, and clinical research overview requirements needed to meet standards of conduct for research involving human subjects. 

While many of these research publications identified signals of potential clinical use in diagnosis for specific diseases and conditions, none of the studies offered the type of confirmatory evidence that are required for medical use; at a minimum, evidence required would include prospective randomized studies. Therefore, this nascent type of diagnostic application research using large patient internet search data sets needs additional sponsorship to support infrastructure, analytic approaches, and importantly, innovative study design that enables prospective data collections to avoid bias and ultimately better understand the clinical efficacy and utility of this practice. 

Further information can be found at the Exploring Consumer & Patient Internet Search Data to Improve Diagnosis Grant Program webpage . Innovation Horizons provided the research and analysis with support from the Gordon and Betty Moore Foundation. 

BREAKING: Political consultant who admitted to deepfaking Biden's voice in primaries is indicted

Vegetarian and vegan diets linked to lower risk of heart disease, cancer and death, large review finds

A plant-based diet is associated with a reduced risk of heart disease, cancer and death, according to a large-scale review published Wednesday. 

The research , which appears in the journal PLOS ONE, analyzed the results of nearly 50 studies published from 2000 to 2023.

The studies examined the health effects of either vegetarian diets or vegan regimens, which restrict any food derived from animals, including dairy.

A clear consensus emerged: Both eating patterns were associated with a lower risk of cancer and ischemic heart disease (heart problems caused by narrowed arteries). In particular, the diets seemed to reduce the risk of prostate cancer and gastrointestinal cancers like colon cancer. Vegetarian diets were also linked to a lower risk of dying from cardiovascular disease.

In addition, plant-based diets were associated with a reduction in risk factors for heart disease and cancer, including high body weight, inflammation and LDL or “bad” cholesterol. 

“This research shows, in general, that a plant-based diet can be beneficial, and taking small steps in that direction can make a difference,” said Matthew Landry, one of the review’s authors and an assistant professor of population health and disease prevention at the University of California, Irvine.

“You don’t have to go completely vegan to see some of these benefits,” he added. “Even reducing a day or two per week of animal-based consumption can have benefits over time.”

However, Dr. Walter Willett, a professor of epidemiology and nutrition at the Harvard T.H. Chan School of Public Health, pointed out that not everyone who follows a plant-based diet eats the same foods, so levels of healthiness still vary.

“A vegetarian diet could be based primarily on refined starches and sugar, which we see to be the worst dietary pattern,” Willett, who was not involved in the new research, said in an email. 

A healthy plant-based diet, he said, should consist mostly of whole grains, fruits, vegetables, nuts, soy, beans and non-hydrogenated plant oils. 

Why are plant-based diets so healthy?

Researchers are still investigating the mechanisms through which plant-based diets lower the risk of disease. 

Some of it may have to do with preventing obesity, which is linked to heart disease and certain cancers . But the benefits likely extend beyond that, Landry said. 

“Some of it is independent of weight. Even when weight is maintained or doesn’t change, we still see reductions in some of these other clinical health outcomes, especially when it relates to cardiovascular disease,” he said.

One possible reason is that many fruits and vegetables are high in anti-inflammatory nutrients and antioxidants, which can reduce plaque buildup in the arteries.

Plant-based diets also tend to be high in fiber, which helps lower bad cholesterol, said Brie Turner-McGrievy, a professor of health promotion, education and behavior at the University of South Carolina. She published a study in 2014 which found that plant-based diets can reduce risk factors for heart disease, stroke and Type 2 diabetes. The research was included in the new review.

“Soluble fiber that’s found in things like beans and oats is really a powerful tool to help lower LDL cholesterol levels,” she said.

Turner-McGrievy noted, though, that much of that benefit can only be achieved through eating whole foods: “It’s not like you can take a fiber supplement and hope to have these same outcomes.”

Another benefit of a plant-based diet may come simply from the absence of meat, she said. People who are vegan tend to consume less saturated fat than meat eaters. 

“It’s just really hard to lower your saturated fat intake if you’re consuming animal-based foods,” Turner-McGrievy said. “Cheese, for example, is the No. 1 source of saturated fat in the diet.”

Processed meat products such as bacon or salami are also known to raise the risk of cancer , according to the World Health Organization. The agency considers red meat in general to be a “probable human carcinogen.”

Is a vegan or vegetarian diet right for everyone?

According to the Academy of Nutrition and Dietetics, vegetarian and vegan diets are adequate and healthy at all stages of life , including pregnancy, childhood and older adulthood. 

But the new review stopped short of recommending plant-based diets for everyone. 

“During pregnancy, it’s not recommended based on the data that we have to use a strict vegetarian diet,” said Dr. Federica Guaraldi, one of the review’s authors and an endocrinologist at the IRCCS Institute of Neurological Sciences of Bologna in Italy. 

Guaraldi and her co-authors found that the plant-based regimens studied didn’t lower the risk of gestational diabetes or hypertension in pregnant women. One study included in the review suggested that pregnant women who followed a vegetarian diet had lower levels of zinc — which is important for children's growth, development and immune function — than those who ate meat. Another study in the review found that vegetarian mothers had an increased risk of delivering babies with low birthweights. 

The review's authors also cautioned that plant-based diets might lead to vitamin B12 deficiencies in the general population. Landry said that can be addressed by taking a B12 supplement.  

“From my perspective as a dietitian, a healthy plant-based diet — either vegetarian or vegan — can really meet just about all your vitamin and mineral needs,” he said. 

Aria Bendix is the breaking health reporter for NBC News Digital.

Understanding Artificial Intelligence with the IRB: Ethics and Advice

Understanding artificial intelligence with the irb: ethical considerations and advice for responsible research in the ai era, as ai tools become more accessible, tc irb discusses the ethics and considerations when using ai in research protocols..

With the surge of help from Generative AI research tools, nowadays is certainly “the most exciting time to be a researcher”, said Shwetak Patel, director of Google’s health technologies and a professor at the University of Washington (Jones, 2023). Researchers now have access to various platforms like Elicit and Consensus which curate a customized archive to assist with literature review, and even to a data analysis tool by ChatGPT. In the middle of this revolutionary era for AI research tools, researchers should consider the ethical impact of AI. This blog post will discuss the ethics and risks involved with using AI in research. We will discuss where the data comes from and the black box AI is utilizing. 

Where Does the Data that AI Use Comes From? To make AI generate answers, engineers first feed vast datasets to AI, a method known as machine learning. Data scraping is the stem of the datasets necessary for training machine learning models. Data scraping involves extracting information from sources such as social media pages and video-sharing sites. Large AI companies often deploy automatic data scraping technology extensively, raising ethical questions and doubts about the origin and usage of the collected data (Macapinlac, 2019). Two significant concerns are 1. the use of copyrighted material in AI training datasets, and 2. Violation of private data, both without proper permission.

First, is the issue of copyright infringement. When collecting large amounts of data to train AI, especially through automated methods, there's a risk of overlooking copyright issues due to the massive volume of data (Riley, 2018). With the rise of generative AI for profit, some decided to tackle this process. An example is Stability AI's Stable Diffusion, a text-to-image generator, which uses datasets from a non-profit organization funded by Stability AI. An investigation revealed that their dataset contained over a million images from sources like Pinterest, WordPress blogs, Flickr, Getty, and DeviantArt without permission, raising questions about copyright infringement. As a result, Getty Images filed a lawsuit against Stability AI over using their copyright issues (Vincent, 2023). This does not only go for companies but is way more critical for individual content creators, who often rely on the integrity and proper use of their work for their livelihood.

In addition to the concerns of copyright infringement, there’s the pressing issue of privacy violation in data scraping. When the data is scrapped from people’s private social media to train the AI model, the data inevitably contains “private information, including personally identifiable information, from hundreds of millions of internet users, including children of all ages, without their informed consent or knowledge.” (Reily, 2023). OpenAI, the company that created chat GPT, is facing a lawsuit for scraping private information from millions of internet users thereby breaching privacy without consent. “They’re taking personal data that has been shared for one purpose and using it for a completely different purpose without the consent of those who shared the data,” said Timothy Edgar, professor of practice of computer science at Brown University. “It is by definition, a privacy violation, or at least an ethical violation, and it might be a legal violation.” This not only is a privacy violation but stems further into a deeper problem when it’s generative AI. The generated answers when a random user asks questions could include private information, and it’ll be difficult to claw back the violated data (Reily, 2023). Considering the ethical conundrum of AI, researchers utilizing generative AI tools must be mindful of these ethical considerations, ensuring they respect copyright laws and the rights of content creators. 

The Black Box Problem: How Does AI Make Decisions?

Now that we understand the ethical challenges associated with the types of data used to train AI, there's another crucial aspect that remains unclear. How do these AI models function once they are trained with vast amounts of data? What processes do they use to make decisions? Many AIs operate as "black boxes". This “black box problem”, while the term itself is still undefined and under discussion, occurs whenever the reasons why an AI decision-maker has arrived at its decision are not understandable because the system itself is not understandable (Wadden, 2023). This issue can lead to complex ethical issues, as seen in 2015 when the Mount Sinai Hospital research team’s use of deep learning on patient records led to the development of Deep Patient (Miotto et al., 2016). The Deep Patient system could predict psychiatric disorders like schizophrenia without revealing how it reached these conclusions, leaving doctors puzzled about its decision-making process. This case raises ethical concerns about how physicians can confidently inform patients about potential health issues without understanding the AI's reasoning.

Using black box technology creates a worse issue when used in contexts without transparency. Since the training data contains human bias, AI can reproduce or even exacerbate the bias leading to social issues. For instance, an AI was used to predict the likelihood of committing a future crime, and a black male with a previous record of petty theft was rated higher than a white male who had been convicted of armed robbery, mirroring the prevalent social bias (Angwin et al., 2016). Of course, we cannot blame AI for magnifying the bias as it is rather a reflection of human bias. However, since AI is hidden under a black veil and we can’t trace the system's thought process and see why it made this decision (Blouin, 2023), researchers should be extra cautious in using AI in their research. Researchers should double-check if their research result using AI is a result of strengthened bias, especially toward a vulnerable population. 

Additionally, the emergence of generative AI raises questions about ownership and commercialization rights. When human creators generate digital art using AI systems, the issue of ownership becomes complex, especially when regulations struggle to keep pace with technological advancements (Riley, 2023). Academia is facing the same challenges. There is a consensus amongst journals and research communities that AI models “cannot meet the requirements for authorship as they cannot take responsibility for submitted work. As non-legal entities, they cannot assert the presence or absence of conflicts of interest nor manage copyright and license agreements,” (Committee on Publication Ethics [COPE], 2023). While AI is not perceived as an ‘author’, researchers should always disclose the usage of AI in their research. Plus, users must assume responsibility and accountability for the content generated by these tools.

Advice for Using AI in Research

As researchers can rely on AI to assist them in their research, participants can also utilize AI tools. They can create bots that can take online surveys for them and receive compensation. Bot infiltration can be seen frequently when conducting online research and requires time and resources to clean the responses (Griffin et al., 2021). Though there is the convenience of using AI, it also comes with risks in securing privacy for online data management. Disclosing participants’ data outside the study can result in severe consequences and may result in damaging researchers’ careers if they avoid using AI safety protocols. Thus, here are a few tips to decrease the risk of or possibly prevent these adverse events.

1) Know the limits of the AI’s privacy

AI can be used to organize data for research and help with general analysis. However, because AI is evolving, most tools use the data inputted by the user to improve its model. It is best to assume that any information shared with the AI will be shown again in the future. To prevent this, researchers should make sure that any data that interacts with the AI is de-identified. Some AI tools may have privacy and confidentiality policies (i.e. users can turn off chat history) but it may not be safe to rely on this information. Never share any personal information. 

2) Use AI to enhance rather than replace your study

It can be tempting to use AI when researchers are in a bind or do not have the time to write protocols. However, this creates disingenuity to the study if researchers allow these tools to do their work. Just as AI tools are improving and becoming more frequent, some tools detect AI usage. Thus, AI should be used to enhance a study, as researchers can receive information they may have missed when conducting initial research and engage in critical thinking. It’s best not to rely on online tools if researchers do not have secure access to them all the time. Researchers should start with their draft and reread it after using AI. We advise you to use AI as a reviewer, not a creator. When it comes to the consent form and other formal documents, try to read aloud what is AI-generated or reviewed before you proceed, to ensure integrity and clarity. Always keep this in mind: AI can “hallucinate”.

3) Know the institutions’ guidelines on using AI

As AI is quite new, some institutions may not be familiar with or accept the usage of AI. It may violate its code of conduct and result in negative outcomes for the researcher’s career if used carelessly. Thus, it is important to ensure that the AI is approved by institutions and their IRB.  Researchers should consult the “Considerations for IRB Review of Research Involving Artificial Intelligence” resource as it provides guidance for IRB reviewers on how to engage with researchers who propose the use of AI in their studies.

Case: Koko Care’s -  Always disclose and receive consent for AI usage

In January 2023, Rob Morris, co-founder of the online emotional support service Koko, shared results from a contentious experiment. He had GPT-3, an AI, compose responses fully or partially for about 4,000 people seeking mental and emotional support, who believed they were communicating with human volunteers. Although initial satisfaction was high, it plummeted once users learned responses were AI-generated, perceived as 'inauthentic and empty.' Criticism arose not from the result, but because of the process. Users, often in mental health crises, weren't informed they were interacting with AI and could not opt out except by ignoring the responses. “People in mental pain could be made to feel worse, especially if the AI produces biased or careless text that goes unreviewed”, said Leslie Wolf, a Georgia State University law professor (Ingram, 2023). Following the backlash, Morris noted Koko's plans to implement a third-party IRB (Institutional Review Board) process for reviewing product changes. This incident underscores the ethical importance of informed consent in research, especially with AI's inherent biases and privacy concerns. It is a reminder for researchers to responsibly use AI, particularly in studies involving vulnerable groups, and consult resources like “Considerations for IRB Review of Research Involving Artificial Intelligence” for guidance.

Final Thoughts

In conclusion, the growing role of AI in research brings both unparalleled opportunities and significant ethical considerations. While AI tools offer invaluable assistance, researchers must navigate the ethical landscape carefully. Key aspects like data origin, privacy, and the black-box nature of AI decision-making necessitate a thoughtful approach to ensure ethical compliance and respect for individual rights. Remember, only humans can infuse elements of care, intuition, and at times, illogical but necessary decisions into research. Therefore, AI should be viewed not as a replacement but as a supportive tool, augmenting human insight and diligence in the pursuit of knowledge.

Accessible version of the infographic

— Jooyoung Jeon, M.A. & Diana Bae, B.A.

Published Tuesday, May 7, 2024

Institutional Review Board

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* Phone: 212-678-4105 * Email:   [email protected]

Appointments are available by request . Make sure to have your IRB protocol number (e.g., 19-011) available.  If you are unable to access any of the downloadable resources, please contact  OASID via email [email protected] .

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Research: What Companies Don’t Know About How Workers Use AI

• Jeremie Brecheisen

Three Gallup studies shed light on when and why AI is being used at work — and how employees and customers really feel about it.

Leaders who are exploring how AI might fit into their business operations must not only navigate a vast and ever-changing landscape of tools, but they must also facilitate a significant cultural shift within their organizations. But research shows that leaders do not fully understand their employees’ use of, and readiness for, AI. In addition, a significant number of Americans do not trust business’ use of AI. This article offers three recommendations for leaders to find the right balance of control and trust around AI, including measuring how their employees currently use AI, cultivating trust by empowering managers, and adopting a purpose-led AI strategy that is driven by the company’s purpose instead of a rules-heavy strategy that is driven by fear.

If you’re a leader who wants to shift your workforce toward using AI, you need to do more than manage the implementation of new technologies. You need to initiate a profound cultural shift. At the heart of this cultural shift is trust. Whether the use case for AI is brief and experimental or sweeping and significant, a level of trust must exist between leaders and employees for the initiative to have any hope of success.

• Jeremie Brecheisen is a partner and managing director of The Gallup CHRO Roundtable.

Partner Center

Peer Reviewed

US-skepticism and transnational conspiracy in the 2024 Taiwanese presidential election

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Taiwan has one of the highest freedom of speech indexes while it also encounters the largest amount of foreign interference due to its contentious history with China. Because of the large influx of misinformation, Taiwan has taken a public crowdsourcing approach to combatting misinformation, using both fact-checking ChatBots and public dataset called CoFacts. Combining CoFacts with large-language models (LLM), we investigated misinformation across three platforms (Line, PTT, and Facebook) during the 2024 Taiwanese presidential election. We found that most misinformation appears within China-friendly political groups and attacks US-Taiwan relations through visual media like images and videos. A considerable proportion of misinformation does not question U.S. foreign policy directly. Rather, it exaggerates domestic issues in the United States to create a sense of declining U.S. state capacity. Curiously, we found misinformation rhetoric that references conspiracy groups in the West.

Program in Quantitative Social Science, Dartmouth College, USA

Department of Political Science, University of Nevada Las Vegas, USA

Department of Computer Science, Barnard College, USA

Research Questions

• What are the misinformation narratives surrounding the election in Taiwan and how do they target international relations with the United States?
• What geographical or temporal patterns emerge from misinformation data?
• Who are the targets of these misinformation narratives and through what modalities?

Essay Summary

• We leveraged a dataset of 41,291 labeled articles from Line, 911,510 posts from Facebook, and 2,005,972 posts and comments from PTT to understand misinformation dynamics through topic modeling and network analysis.
• The primary form of misinformation is narratives that attack international relations with the United States (henceforth referred to as US-skepticism), specifically referencing the economy, health policy, the threat of war through Ukraine, and other U.S. domestic issues.
• Temporal and spatial evidence suggests VPN-based coordination, focused on U.S. issues and addresses.
• Misinformation is most common among pan-Blue and ROC identity groups on social media and is spread through visual media. These groups share many themes with conspiracy groups in Western countries.
• Our study shows the prevalence of misinformation strategies using visual media and fake news websites. It also highlights how crowdsourcing and advances in large-language models can be used to identify misinformation in cross-platform workflows.

Implications

According to Freedom House, Taiwan has one of the highest indices for free speech in Asia (Freedom House, 2022). Additionally, due to its contentious history with China, it receives significant foreign interference and misinformation, especially during its presidential elections. Due to the large influx of dis- and misinformation, Taiwan has developed many strategies to counter misleading narratives, including fact-checking ChatBots on its most popular chatroom app (Chang et al., 2020). Under this information environment, the 2024 Taiwanese presidential election emerged as one of the most divisive elections in Taiwan’s history, featuring at one point a doubling of presidential candidates in a typically two-party race, from two to four. As such, Taiwan is regarded as a “canary for disinformation” against elections in 2024, as a first indicator to how foreign interference may take place in other democracies (Welch, 2024).

In this paper, we study the misinformation ecosystem in Taiwan starting a year prior to the election. First, our findings highlight the interaction between misinformation and international relations. As was reported in The Economist and The New York Times , a considerable portion of the misinformation spread in Taiwan before the 2024 election is about US-skepticism, which aims at undermining the reputation of the United States among Taiwanese people (“China is flooding Taiwan with disinformation,” 2023; Hsu, Chien, and Myers, 2023). This phenomenon is significant because it does not target specific candidates or parties in the election but may indirectly influence the vote choice between pro- and anti-U.S. parties. Given the US-China global competition and the Russia-Ukraine ongoing conflict, the reputation of the United States is crucial for the strength and reliability of democratic allies (Cohen, 2003). Hence, it is not surprising that misinformation about the United States may propagate globally and influence elections across democracies. However, our findings surprisingly show that US-skepticism also includes a considerable number of attacks on U.S. domestic politics. Such content does not question the U.S. foreign policy but undermines the perceived reliability and state capacity of the United States. Here, s tate capacity is defined as whether a state is capable of mobilizing its resources to realize its goal, which is conceptually different from motivation and trust.

US-skepticism is commonly characterized as mistrusting the motivations of the United States, as illustrated in the Latin American context due to long histories of political influence (see dependency theory; Galeano, 1997), but our findings suggest that perceived U.S. state capacity is also an important narrative. As most foreign disinformation arises from China, this indicates a greater trend where authoritarian countries turn to sharp power tactics to distort information and defame global competitors rather than winning hearts and minds through soft power. Sharp power refers to the ways in which authoritarian regimes project their influence abroad to pierce, penetrate, or perforate the informational environments in targeted countries (Walker, 2018). In Taiwan’s case, China may not be able to tell China’s story well, but can still influence Taiwanese voters by making them believe that the United States is declining. Our findings suggest that future work analyzing the topics and keywords of misinformation in elections outside the United States should also consider the US-skepticism as one latent category, not just the politicians and countries as is common with electoral misinformation (Tenove et al., 2018). These findings are corroborated by narratives identified by a recent report including drug issues, race relations, and urban decay (Microsoft Threat Intelligence, 2024).

Additionally, our research investigates both misinformation and conspiracy theories, which are closely related. Whereas misinformation is broadly described as “false or inaccurate information” (Jerit & Zhao, 2020), a conspiracy theory is the belief that harmful events are caused by a powerful, often secretive, group. In particular, conspiracy communities often coalesce around activities of “truth-seeking,” embodying a contrarian view toward commonly held beliefs (Enders et al., 2022; Harambam, 2020; Konkes & Lester, 2017). Our findings also provide evidence of transnational similarities between conspiracy groups in Taiwan and the United States. Whereas the domestic context has been explored (Chen et al., 2023; Jerit & Zhao, 2020), the intersection of partisanship and conspiracy groups as conduits for cross-national misinformation flow deserves further investigation.

Second, our findings reemphasize that an IP address is not a reliable criterion for attributing foreign intervention.  Previous studies on Chinese cyber armies show that they use a VPN for their activities on Twitter (now X) (Wang et al., 2020) and Facebook (Frenkel, 2023). Commonly known as the Reddit of Taiwan, PTT is a public forum in Taiwan that by default contains the IP address of the poster. Our analysis of PTT located a group of accounts with US IP addresses that have the same activity pattern as other Taiwan-based accounts. Therefore, it is likely that these accounts use VPN to hide their geolocation. Our results provide additional evidence that this VPN strategy also appears on secondary and localized social media platforms. Our results suggest that the analysis of the originating location of misinformation should not be based entirely on IP addresses.

Third, our findings show that text is far from the only format used in the spread of misinformation. A considerable amount of misinformation identified on Facebook is spread through links (47%), videos (21%), and photos (15%). These items may echo each other’s content or even feature cross-platform flow. Proper tools are needed to extract and juxtapose content from different types of media so that researchers can have a holistic analysis of the spread and development of misinformation (Tucker et al., 2018). Such tools are urgent since mainstream social media has adopted and highly encouraged short videos—a crucial area for researchers to assess how misinformation spreads across platforms in the upcoming year of elections. This understanding is also important for fact-check agencies because they must prepare for collecting and reviewing information on various topics found in multiple media types across platforms. Crowdsourcing, data science, expert inputs, and international collaboration are all needed to deal with multi-format misinformation environments.

With prior studies showing that the aggregated fact checks (known as wisdom of the crowds) perform on par with expert ratings (see Arechar et al., 2023; Martel et al., 2023), our case study also evidences how crowdsourcing and LLM approaches can not only quickly fact-check but also summarize larger narrative trends. In Taiwan, this takes form of the CoFacts open dataset, which we use to identify misinformation narratives. CoFacts is a project initiated by g0v (pronounced “gov zero”), a civic hacktivism community in Taiwan that started in 2012. CoFacts started as a fact-checking ChatBot that circumvents the closed nature of chatroom apps, where users can forward suspicious messages or integrate the ChatBot into private rooms. These narratives are then sent to a database. Individual narratives are subsequently reviewed by more than 2,000 volunteers, including teachers, doctors, students, engineers, and retirees (Haime, 2022). As a citizen-initiated project, it is not affiliated with any government entity or party.

Crucially, these reviews provide valuable labels that are used to train AI models and fine-tune LLMs. The dataset is available open source on the popular deep-learning platform HuggingFace. Just as AI and automation can be used to spread misinformation (Chang, 2023; Chang & Ferrara, 2022; Ferrara et al., 2020; Monaco & Woolley, 2022), it can also help combat “fake news” through human-AI collaboration.

Finding 1: The primary form of misinformation  is narratives that attack international relations with the United States (henceforth referred to as US-skepticism), specifically referencing the economy, health policy, the threat of war through Ukraine, and other U.S. domestic issues.

The status quo between China and Taiwan is marked by Taiwan’s self-identification as a sovereign state, which is in contrast to China’s view of Taiwan as part of its territory under the “One China” policy. As brief context, China has claimed Taiwan as its territory since 1949, but the United States has helped maintain the status quo and peace after the outbreak of the Korean War in 1950. After democratization in 1987, Taiwan’s politics have been dominated by a clear blue-green division. The blue camp is led by Kuomintang (Nationalist Party, KMT hereafter), the founding party of the Republic of China (ROC, the formal name of Taiwan’s government based on its constitution) who was defeated by the People’s Republic of China (PRC) and retreated to Taiwan in 1949. The green camp is led by the Democratic Progressive Party (DPP), which pursues revising the ROC Constitution and changing the country’s name to Taiwan. The political cleavage between the blue and green camps is dictated by Taiwan’s relationship with the PRC and the United States. The blue camp’s position is that the PRC and ROC are under civil war but belong to the same Chinese nation, and thus the blue camp appreciates military support from the United States while enhancing economic and cultural cooperation with the PRC. The green camp believes that the necessary conditions for Taiwan to be free and independent are to stand firmly with the United States and maintain distance from the PRC. After 2020, the two major camps’ insufficient attention to domestic and social issues caused the rise of nonpartisans and a third party, the Taiwan People’s Party (TPP or the white camp), which strategically avoids discussing foreign policies. In the 2024 election, the ruling DPP party (green) was reelected with 40% of votes for the third consecutive presidency (from 2016 to 2028), while KMT (blue) and TPP (white) received 33% and 26% of votes, respectively.

The U.S. “One China” policy since 1979 indicates that the United States opposes any change to the status quo unless it is solved peacefully. This has motivated the PRC to persuade Taiwanese citizens to support unification using misinformation targeted at China-friendly political groups, as the cost of unification would be greatly reduced if sufficient Taiwanese citizens opposed U.S. military intervention. This history between the United States and Taiwan serves as the foundation of US-skepticism. In the literature, US-skepticism in Taiwan is composed of two key psychological elements: trust and motivation (Wu & Lin, 2019; Wu, 2023). First, many Taiwanese no longer trust the United States after the United States switched diplomatic ties from Taiwan (ROC) to the PRC in 1979. Many blue-camp supporters doubt the commitment of the United States to send troops should China invade, per the Taiwan Relations Act (Wu & Lin, 2019). Second, Taiwanese citizens question Taiwan’s role as a proxy in a potential war with China instead of sincerely protecting democracy and human rights in Taiwan (Wu, 2023).

The CoFacts dataset contains 140,314 articles submitted by Line users, which are then fact-checked by volunteers as rumor (47%), not a rumor (21%), not an article (19%), and opinion (13%). Here, rumor is synonymous with misinformation. Using the CoFacts dataset, we trained a BERTopic model to identify 34 forms of misinformation and then ranked them by their overlap with the word “elections” in Mandarin Chinese (George & Sumathy, 2023; Nguyen et al., 2020). Table 1 shows the top nine narratives.

Many of these narratives are directly related to political parties or the democratic process. For instance, the highest-ranked topic is attacking the incumbent party (the DPP) at 18.1%, which contains 2,371 total posts. The subsequent misinformation topics focus on policy issues and specific narratives—international relations, issues of marriage and birth rate, vaccines, nuclear energy, biometrics, egg imports, and the war in Ukraine. These are known cleavage issues and overlap with the eight central concerns during the election cycle—economic prosperity, cross-strait affairs, wealth distribution, political corruption, national security, social reform/stability, and environmental protection (Achen & Wang, 2017; Achen & Wang, 2019; Chang & Fang, 2023).

We focus on the third type of misinformation, which is the relationship between Taiwan, the United States, and China. US-skepticism is not only the largest at 10,826 individual posts, but one flagged by journalists, policymakers, and politicians as one of the most crucial themes. This is a relatively new phenomenon in terms of proportion, which aims to sow distrust toward the United States (“China is flooding Taiwan with disinformation,” 2023). In contrast, questioning the fairness of process (i.e. ballot numbers) and policy positions (i.e. gay marriage) are common during elections. However, US-skeptical misinformation diverges in that there is no explicit political candidate or party targeted. By sampling the topic articles within this category and validating using an LLM-summarizer through the ChatGPT API, we identified three specific narratives:

(a) The United States and the threat of war: Ukraine intersects frequently in this topic, with videos of direct military actions. Example: “Did you hear former USA military strategist Jack Keane say the Ukrainian war is an investment. The USA spends just $66,000,000,000 and can make Ukraine and Russia fight…  Keane then mentions Taiwan is the same, where Taiwanese citizens are an ‘investment’ for Americans to fight a cheap war. The USA is cold and calculating, without any actual intent to help Taiwan!”

(b) Economic atrophy due to fiscal actions by the United States: These narratives focus on domestic policy issues in Taiwan such as minimum wage and housing costs. Example: “The USA printed 4 trillion dollars and bought stocks everywhere in the world, including Taiwan, and caused inflation and depressed wages. Be prepared!”

(c) Vaccine supply and the United States: While some narratives focus on the efficacy of vaccines, several describe the United States intentionally limiting supply during the pandemic. Example: “Taiwanese Dr. Lin is a leading scientist at Moderna, yet sells domestically at $39 per two doses, $50 to Israel. Taiwan must bid at least $60! The United States clearly does not value Taiwan.”

These narratives reveal a new element to US-skepticism: state capacity. As previously mentioned, state capacity is defined as whether a state is capable of mobilizing its resources to realize its goal. The Ukraine war and vaccine supply narratives both question the United States’ motivations in foreign policies and perceived trustworthiness. Meanwhile, the economic atrophy narrative is based on the United States’ domestic budgetary deficit and downstream impact on Taiwanese economy. These narratives frame U.S. state capacity as declining and imply that the United States could no longer realize any other commitment due to its lack of resources and capacity. The goal of such a narrative is to lower the Taiwanese audience’s belief that the United States will help. But such a narrative does not include keywords of its target group (e.g., Taiwan) nor the PCR’s goal (e.g., unification) and only works through framing and priming as an example of sharp power. 

The specific focus of misinformation narratives related to the United States is composed of Ukraine (28.8%), the economy and fiscal policies (33.1%), technology (25.2%), and vaccine supply (9.9%). Misinformation related to state capacity takes up approximately 52.4%, more than half of all narratives (see Figure A1, part a in the Appendix). In all narratives, political parties are only referenced 27.8% of the time with the DPP the primary target (26.2%), which is almost half of the proportion for state capacity. China is only mentioned in tandem with the United States in 38.4% of the posts (see Figure A1, part b in the Appendix).

Finding 2: Temporal and spatial evidence suggests VPN-based coordination, focused on U.S. issues and addresses.

Once we identified the top misinformation narratives using Line, we investigated information operations or coordination. Line is one of Taiwan’s most popular communication apps featuring chatrooms (similar to WhatsApp), with 83% usage. One limitation of Line is that although we can analyze message content, Line chatrooms can be seen as conversations behind “closed doors”—platforms cannot impose content moderation and researchers have no access to the users themselves nor to the private chatroom in which users engage with misinformation (Chang et al., 2020). PTT, on the other hand, provides a public forum-like environment in which users can interact. Figure 1 shows the co-occurrence network of users who post comments under the same forum. Each circle (node) represents a user who posts on PTT. If two users make mutual comments on more than 200 posts, then they are connected (form a tie). Intuitively, this means if two users are connected or “close” to each other by mutual connections, then they are likely coordinating or have extremely similar behaviors. The placement of the users reflects this and is determined by their connections.

Using the Louvain algorithm (Traag, 2015), a common method to identify communities on social networks, five communities emerged from our dataset. Each community is colored separately, with clear clusters, except for teal which is more integrated. In particular, the yellow cluster is significantly separate from the others. This means they share significant activity amongst their own community, but less so with other communities. This suggests premeditated coordination rather than organic discussion, as the users would have to target the same post with high frequency. Prior studies have shown analyzing temporal patterns can provide insight into information operations. Specifically, overseas content farms often follow a regular cadence, posting content before peak hours in Taiwan on Twitter (Wang et al., 2020) and YouTube (Hsu & Lin, 2023).

To better understand the temporal dynamics on PTT, we plotted the distribution of posts and comments over a 24-hour period. Specifically, we focused on the top two countries by volume—Taiwan and the United States. Figure 2, part a shows the time of posting. Taiwan’s activity increases from 6 in the morning until it peaks at noon (when people are on lunch break), then steadily declines into the night. In contrast, posts from the United States peak at midnight and 8 a.m. Taipei time, which corresponds to around noon and 8 p.m. in New York, respectively. This provides an organic baseline as to when we might expect people to post.

However, in Figure 2, part b, while the distribution for Taiwan (blue) remains unchanged, the peak for the United States (orange) occurs at the same time as Taiwan. One explanation is that users are responding to posts in Taiwan. The second is that users in Asia—potentially China—are using a VPN to appear as if they are in the United States. This coincides with a report by Meta Platforms that found large numbers of CCP-operated Facebook accounts and subsequently removed them (Frenkel, 2023).

The more curious issue is when considering the activity of the yellow group from Figure 1, the temporal pattern (green) shows a sharp increase in activity at 10 a.m., which then coincides with both the peaks for Taiwan (12) and the United States (22). The sudden burst of activity is consistent with prior findings on content farms from China, where posting behavior occurs when content farm workers clock in regularly for work (Wang et al., 2020). While it is difficult to prove the authenticity of these accounts, the structural and temporal aspects suggest coordination. Figure A2 in the appendix shows further evidence of coordination through the frequency distribution of counts for co-occurring posts. For the US-based group, a distribution akin to a power law appears, commonly found within social systems (Adamic & Huberman, 2000; Chang et al., 2023; Clauset et al., 2009). In contrast, the coordinated group features a significantly heavier tail, with a secondary, “unnatural,” peak at around 15 co-occurrences.

To better understand the content of these groups, Table A1 shows the summary of comments of each group and the originating post, using a large-language model for abstractive summarization (see Methods). We report the top points for comments and posts in Table A1. The coordinated community focuses on businessman Terry Gou, who considered running as a blue-leaning independent. The comments attack the incumbent DPP and their stance toward foreign policy. One popular post features President Tsai’s controversial meeting with Kevin McCarthy, then the Speaker of the U.S. House of Representatives. When a journalist asked McCarthy if he would “invite President Tsai to Congress… or… Washington,” McCarthy replied, “I don’t have any invitation out there right now. Today we were able to meet her as she transits through America, I thought that was very productive.” While this was positively framed, the title of the post itself was translated as “McCarthy will not invite Tsai to the United States” (Doomdied, 2023). This takes on a common tactic in misinformation where statements are intentionally distorted to produce negative framings of a particular candidate.

Comments from U.S. IP addresses between 11 a.m. and 2 p.m. focus on the potential alliance between the KMT and TPP. These posts are KMT-leaning with criticism toward both Lai and Ko, who are two oppositional candidates to the KMT. Some users argue that while the Chinese Communist Party (CCP) is a negative force, the United States is not automatically a positive force, as the United States does not explicitly support Taiwan’s international recognition or economic integration. In general, both posts and comments express that Taiwan should not rely too heavily on either China or the United States. This echoes the element of trust in the US-skepticism from the historical experience between ROC and the United States.

Both the U.S.-based and coordinated groups appear as blue-leaning audiences. What differentiates the first and second case is clear evidence of misinformation in the former through inaccurate framing. While US-skepticism may be a valid political stance, if the ambient information environment contains inaccurate information, then the democratic deliberative process is at risk. The case of US-skepticism is also one where stance and truth-value are often conflated, which may influence the process of voter deliberation.

Finding 3: Misinformation is most common among pan-Blue and ROC identity groups on social media and is spread through visual media. These groups share themes with conspiracy groups in Western countries.

Lastly, we considered the groups in which misinformation is common and the way misinformation is delivered. To do so, we queried CrowdTangle using the titles and links from the CoFacts dataset specific to US-Taiwan relations. This yielded 4,632 posts from public groups. Table 2 shows the groups ranked by the total number of misinformation articles identified.

There are two themes to these groups. First, they are often pan-Blue media outlets ( CTI News ), politician support groups ( Wang Yo-Zeng Support Group ), and ROC national identity groups ( I’m an ROC Fan ). The second type is somewhat unexpected but extremely interesting; it consists of groups that espouse freedom of speech ( Support CTI News and Free Speech ) and truth-seeking ( Truth Engineering Taiwan Graduate School ), topics often regarded as conspiracies. These topics are reminiscent of those in the West, such as the rhetoric around “fake news” and “truthers,” and paint a transnational picture of how misinformation coalesces. The second largest group is Trump for the World , which supports a politician known to court conspiracy theory groups such as QAnon. These groups also serve as the “capacity” element of US-skepticism, implying that the United States is in trouble for its domestic issues and is not a reliable partner to Taiwan. Furthermore, these groups have sizable followings—ranging from 8,279 to 43,481. We show the mean, as the total number of members fluctuated over our one-year period.

Lastly, we found that the majority of misinformation contains some form of multimedia, such as video (36%) or photos (15%), as shown in Figure 3, part a. Only 1% is a direct status. This may be due to CrowdTangle not surfacing results from normal users, but the ratio of multimedia to text is quite high. This aligns with extant studies showing the growth of multimodal misinformation (Micallef et al., 2022) and also user behavior in algorithm optimization (Chang et al., 2022; Dhanesh et al., 2022; Pulley, 2020)—posts with multimedia tend to do better than posts with only text.

Moreover, 47% contain a URL. Figure 3, part b shows one of the top domains containing misinformation (beyondnews852.com) after filtering out common domains such as YouTube. The site is named “Beyond News Net” and is visually formatted like a legitimate news site to increase the perceived credibility of information (Flanagin & Metzger, 2007; Wölker & Powell, 2021). The ability to rapidly generate legitimate-looking news sites as a tactic for misinformation may become a challenge for both media literacy and technical approaches to fight misinformation.

We utilized three unique misinformation datasets—Line, Facebook, and PTT—with dates between 01/12/2023 and 11/10/2023. The CoFacts dataset includes 140,193 received messages, 96,432 that have been labeled as misinformation, facts, opinion, or not relevant. Of this, 41,564 entries are misinformation. The CoFacts dataset is not only methodologically useful but exemplifies a crowd-sourced approach to fact-checking misinformation as an actual platform intervention. Moreover, it is public and transparent, allowing for replicability. Using a subset of articles and posts containing misinformation, we trained a topic model using BERTopic (Grootendorst, 2022). On a high level, using BERTopic involves five steps: 1) extract embeddings using a sentence transformer, 2) reduce dimensionality, 3) cluster reduced embeddings, 4) tokenize topics, and 5) create topic representation.

We conducted several trials, experimenting with parameters such as different sentence transformer models and minimum cluster sizes for the HDBSCAN clustering algorithm. The model used to extract topics for this paper utilized paraphrase-multilingual-MiniLM-L12-v2 for our sentence embedding model (Reimers & Gurevych, 2019), had a minimum cluster size of 80 for the clustering algorithm, and used tokenize_zh for our tokenizer. Our model yielded 34 topics. We also trained a model based on latent-Dirichlet allocation (LDA) (Blei et al., 2003), but found the BERTopic results to be more interpretable. We then labeled all messages to indicate whether they included reference to the election or not, and ranked the topics by their election-related percentage to measure electoral salience. For our subsequent analysis, we focused on topic 3 (see Table 1), which captures general discourse about the relations between the United States, China, and Taiwan.

The Facebook dataset was extracted using CrowdTangle. We queried posts containing links and headlines from topic 3. We also cross-sectioned these links and headlines with a general election-based dataset with 911,510 posts. This yielded a total of 4,632 of posts shared on public Facebook groups and 227,125 engagements. Due to privacy concerns, it is not possible to obtain private posts from users on their own Facebook timelines, private groups, or messages. However, public groups are a good proxy for general discourse, in addition to providing ethnic or partisan affiliations via their group name (Chang & Fang, 2023). In other words, while CoFacts provides the misinformation narratives, Facebook public groups give insight into the targets of misinformation.

Lastly, we scraped PTT using Selenium. Commonly known as the Reddit of Taiwan, PTT is unique in that it contains the IP address of the poster, though this could be shrouded by proxy farms or VPNs. First, we scraped all posts that contained reference to the United States and the election, which yielded 22,576 posts and 1,983,396 comments, all with IP addresses, addresses provided by PTT, and the time of posting. We expanded the scope of this analysis as we were interested in the general discourse directly related to the United States, and the geospatial and temporal patterns that arose. 

Due to the large amount of data, there are three general approaches we could have taken—local extractive summarization with LLMs, local abstractive summarization with LLMs, and server-based abstractive summarization (such as ChatGPT). Local extractive summarization is a method that embeds each of the input sentences and then outputs five of the most representative sentences. However, this approach is often too coarse, as it returns sentences with the highest centrality but does not summarize general themes across all the different comments or posts. On the other hand, abstractive summarization works by considering the entire context by ingesting many documents and then summarizing across them. This provides a more generalized characterization of key themes. However, the input size is the primary bottleneck as large-language models can only ingest so many tokens (or words), which also need to be held in memory—the case for our project, as we are summarizing more than 10,000 posts.

To circumvent these issues, we sampled the maximum number of posts or comments that could fit within 16,000 tokens and then made a query call using the ChatGPT API. This provided a summary based on a probabilistic sample of the posts and comments.

• / Elections

Cite this Essay

Chang, H. C. H., Wang, A. H. E., & Fang Y. S. (2024). US-skepticism and transnational conspiracy in the 2024 Taiwanese presidential election. Harvard Kennedy School (HKS) Misinformation Review . https://doi.org/10.37016/mr-2020-144

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No funding has been received to conduct this research.

Competing Interests

The authors declare no competing interests.

No human subjects were included in this study.

This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided that the original author and source are properly credited.

Data Availability

All materials needed to replicate this study are available via the Harvard Dataverse: https://doi.org/10.7910/DVN/5SPGDY . The Cofacts database is available on HuggingFace and Facebook via CrowdTangle per regulation of Meta Platforms.

Acknowledgements

H. C. would like to thank Brendan Nyhan, Sharanya Majumder, John Carey, and Adrian Rauschfleish for their comments. H. C. would like to thank the Dartmouth Burke Research Initiation Award.

All authors contributed equally.

News & Media Relations

College of business, csu leads comprehensive review of wildfire research in collaboration with stanford university.

Contact for reporters: Allison Sylte [email protected] Cell: (720)-849-1907

The huge, long-lasting wildfires that have become increasingly common in recent years can cause changes in soil chemistry that affect water contamination, air quality and plant growth. These changes, however, are poorly monitored and rarely factor into post-fire recovery efforts or risk assessments, according to a CSU-led article  published May 14 in  Nature Reviews Earth & Environment .

The literature review, initiated and led by Thomas Borch, a soil chemist and professor in CSU’s Department of Soil and Crop Sciences, found that better techniques are needed to monitor fire-induced changes in soil chemistry. This enhanced monitoring could inform decisions on how to treat drinking water sourced from burned areas, support reforestation, and protect workers against toxins during post-fire cleanup, rebuilding or revegetation.

The work was conducted in collaboration with researchers at Stanford University. CSU doctoral student Jacob VanderRoest and postdoctoral researcher Holly Roth also contributed to the review article.

“A better understanding of the molecular mechanisms in soil can help explain, for instance, why drinking water from a forest fire-impacted watershed is suddenly more toxic, or why a forest is not coming back,” said  Borch , a senior author of the study.

“In our study, we mesh organic and inorganic chemistry together, whereas a lot of fire research will typically just consider one subject area,” said  Claudia Avila , a soil biogeochemist who co-led the study with Alandra Lopez while both researchers were postdoctoral scholars in the lab of  Stanford Doerr School of Sustainability  Professor  Scott Fendorf .

Climate and ecosystem impacts

The review highlights evidence from recent studies suggesting wildfires may release more planet-warming carbon dioxide into the atmosphere than anticipated. Charcoal-like remnants of burned wood and other organic materials, known as black carbon, may not trap carbon dioxide for as long as scientists had hoped.

“Carbon that’s gone through forest fires and becomes black carbon can actually turn more readily into carbon dioxide by microbes than previously thought,” said Fendorf, the Terry Huffington Professor at Stanford.

“From a climate perspective, we still have a poor understanding of how much of the carbon that is left after a fire has the potential to be transformed into greenhouse gasses, such as carbon dioxide,” said Borch, who worked in Fendorf’s lab as a postdoctoral fellow 20 years ago.

Wildfires can have many benefits for ecosystems, the authors note. For example, some fires can increase the nitrogen content in soil organic matter and augment the water solubility of soil organic carbon, setting the stage for regrowth. However, recovery depends on the presence of other chemicals. For instance, certain types of organic molecules formed in soil during fires, called karrikins, are needed for many seeds to germinate. If the local soil chemistry and fire conditions do not produce enough of these karrikins, revegetation may be stunted.

Other research included in the new review has shown that wildfires can double the soil concentration of a group of toxic chemicals known as polycyclic aromatic hydrocarbons, which can induce chemical reactions that inhibit revegetation. These molecular-scale effects could well explain the mystery of vast areas where trees have struggled to reestablish after wildfires in the Rocky Mountains, Borch said.

Wildfires can also alter the chemical properties of inorganic materials such as metals within soils. Fire can change the metals into dangerous forms that readily move through the environment, ending up in the air or nearby water, the authors explained. The collaborators from Stanford University had previously documented high levels of a hazardous form of the metal  chromium at wildfire sites  resulting from heat-induced transformation of naturally occurring, benign forms of chromium. At sites where extremely hot, long-lasting fires cooked soils to high temperatures for extended periods, chromium persisted for many months until the next large rain event.

Other research on chromium indicates that after lower-intensity fires, remnant plant and animal tissue in soil can allow the toxic form of chromium to return to its inert form. Taken together, these studies illustrate the broader reality that wildfire impacts on soil chemistry depend on the intricate nature of the fire and landscape, including fire duration and temperature.

Predicting and mitigating wildfire risks

Broader surveillance and modeling could inform wildfire management decisions and strategies for protecting lives, property and natural resources. Avila offers an example of how this approach to informed stewardship could help prevent the leaching of metals into drinking water supplies.

“By identifying an area that has a high potential for, say, chromium release, we can call for prescribed burns that are lower intensity and reduce the potential for high-intensity, toxin-releasing fires,” said Avila, who is now an assistant professor of environmental and ocean sciences at the University of San Diego.

“If we can grasp the complexity of the intertwined processes that are happening both on the organic and the inorganic side, then that helps give us the ability to predict outcomes for different fire, landscape and geological conditions,” Fendorf said.

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Peer review guidance: a primer for researchers

Olena zimba.

1 Department of Internal Medicine No. 2, Danylo Halytsky Lviv National Medical University, Lviv, Ukraine

Armen Yuri Gasparyan

2 Departments of Rheumatology and Research and Development, Dudley Group NHS Foundation Trust (Teaching Trust of the University of Birmingham, UK), Russells Hall Hospital, Dudley, West Midlands, UK

The peer review process is essential for quality checks and validation of journal submissions. Although it has some limitations, including manipulations and biased and unfair evaluations, there is no other alternative to the system. Several peer review models are now practised, with public review being the most appropriate in view of the open science movement. Constructive reviewer comments are increasingly recognised as scholarly contributions which should meet certain ethics and reporting standards. The Publons platform, which is now part of the Web of Science Group (Clarivate Analytics), credits validated reviewer accomplishments and serves as an instrument for selecting and promoting the best reviewers. All authors with relevant profiles may act as reviewers. Adherence to research reporting standards and access to bibliographic databases are recommended to help reviewers draft evidence-based and detailed comments.

Introduction

The peer review process is essential for evaluating the quality of scholarly works, suggesting corrections, and learning from other authors’ mistakes. The principles of peer review are largely based on professionalism, eloquence, and collegiate attitude. As such, reviewing journal submissions is a privilege and responsibility for ‘elite’ research fellows who contribute to their professional societies and add value by voluntarily sharing their knowledge and experience.

Since the launch of the first academic periodicals back in 1665, the peer review has been mandatory for validating scientific facts, selecting influential works, and minimizing chances of publishing erroneous research reports [ 1 ]. Over the past centuries, peer review models have evolved from single-handed editorial evaluations to collegial discussions, with numerous strengths and inevitable limitations of each practised model [ 2 , 3 ]. With multiplication of periodicals and editorial management platforms, the reviewer pool has expanded and internationalized. Various sets of rules have been proposed to select skilled reviewers and employ globally acceptable tools and language styles [ 4 , 5 ].

In the era of digitization, the ethical dimension of the peer review has emerged, necessitating involvement of peers with full understanding of research and publication ethics to exclude unethical articles from the pool of evidence-based research and reviews [ 6 ]. In the time of the COVID-19 pandemic, some, if not most, journals face the unavailability of skilled reviewers, resulting in an unprecedented increase of articles without a history of peer review or those with surprisingly short evaluation timelines [ 7 ].

Editorial recommendations and the best reviewers

Guidance on peer review and selection of reviewers is currently available in the recommendations of global editorial associations which can be consulted by journal editors for updating their ethics statements and by research managers for crediting the evaluators. The International Committee on Medical Journal Editors (ICMJE) qualifies peer review as a continuation of the scientific process that should involve experts who are able to timely respond to reviewer invitations, submitting unbiased and constructive comments, and keeping confidentiality [ 8 ].

The reviewer roles and responsibilities are listed in the updated recommendations of the Council of Science Editors (CSE) [ 9 ] where ethical conduct is viewed as a premise of the quality evaluations. The Committee on Publication Ethics (COPE) further emphasizes editorial strategies that ensure transparent and unbiased reviewer evaluations by trained professionals [ 10 ]. Finally, the World Association of Medical Editors (WAME) prioritizes selecting the best reviewers with validated profiles to avoid substandard or fraudulent reviewer comments [ 11 ]. Accordingly, the Sarajevo Declaration on Integrity and Visibility of Scholarly Publications encourages reviewers to register with the Open Researcher and Contributor ID (ORCID) platform to validate and publicize their scholarly activities [ 12 ].

Although the best reviewer criteria are not listed in the editorial recommendations, it is apparent that the manuscript evaluators should be active researchers with extensive experience in the subject matter and an impressive list of relevant and recent publications [ 13 ]. All authors embarking on an academic career and publishing articles with active contact details can be involved in the evaluation of others’ scholarly works [ 14 ]. Ideally, the reviewers should be peers of the manuscript authors with equal scholarly ranks and credentials.

However, journal editors may employ schemes that engage junior research fellows as co-reviewers along with their mentors and senior fellows [ 15 ]. Such a scheme is successfully practised within the framework of the Emerging EULAR (European League Against Rheumatism) Network (EMEUNET) where seasoned authors (mentors) train ongoing researchers (mentees) how to evaluate submissions to the top rheumatology journals and select the best evaluators for regular contributors to these journals [ 16 ].

The awareness of the EQUATOR Network reporting standards may help the reviewers to evaluate methodology and suggest related revisions. Statistical skills help the reviewers to detect basic mistakes and suggest additional analyses. For example, scanning data presentation and revealing mistakes in the presentation of means and standard deviations often prompt re-analyses of distributions and replacement of parametric tests with non-parametric ones [ 17 , 18 ].

Constructive reviewer comments

The main goal of the peer review is to support authors in their attempt to publish ethically sound and professionally validated works that may attract readers’ attention and positively influence healthcare research and practice. As such, an optimal reviewer comment has to comprehensively examine all parts of the research and review work ( Table I ). The best reviewers are viewed as contributors who guide authors on how to correct mistakes, discuss study limitations, and highlight its strengths [ 19 ].

Structure of a reviewer comment to be forwarded to authors

Some of the currently practised review models are well positioned to help authors reveal and correct their mistakes at pre- or post-publication stages ( Table II ). The global move toward open science is particularly instrumental for increasing the quality and transparency of reviewer contributions.

Advantages and disadvantages of common manuscript evaluation models

Since there are no universally acceptable criteria for selecting reviewers and structuring their comments, instructions of all peer-reviewed journal should specify priorities, models, and expected review outcomes [ 20 ]. Monitoring and reporting average peer review timelines is also required to encourage timely evaluations and avoid delays. Depending on journal policies and article types, the first round of peer review may last from a few days to a few weeks. The fast-track review (up to 3 days) is practised by some top journals which process clinical trial reports and other priority items.

In exceptional cases, reviewer contributions may result in substantive changes, appreciated by authors in the official acknowledgments. In most cases, however, reviewers should avoid engaging in the authors’ research and writing. They should refrain from instructing the authors on additional tests and data collection as these may delay publication of original submissions with conclusive results.

Established publishers often employ advanced editorial management systems that support reviewers by providing instantaneous access to the review instructions, online structured forms, and some bibliographic databases. Such support enables drafting of evidence-based comments that examine the novelty, ethical soundness, and implications of the reviewed manuscripts [ 21 ].

Encouraging reviewers to submit their recommendations on manuscript acceptance/rejection and related editorial tasks is now a common practice. Skilled reviewers may prompt the editors to reject or transfer manuscripts which fall outside the journal scope, perform additional ethics checks, and minimize chances of publishing erroneous and unethical articles. They may also raise concerns over the editorial strategies in their comments to the editors.

Since reviewer and editor roles are distinct, reviewer recommendations are aimed at helping editors, but not at replacing their decision-making functions. The final decisions rest with handling editors. Handling editors weigh not only reviewer comments, but also priorities related to article types and geographic origins, space limitations in certain periods, and envisaged influence in terms of social media attention and citations. This is why rejections of even flawless manuscripts are likely at early rounds of internal and external evaluations across most peer-reviewed journals.

Reviewers are often requested to comment on language correctness and overall readability of the evaluated manuscripts. Given the wide availability of in-house and external editing services, reviewer comments on language mistakes and typos are categorized as minor. At the same time, non-Anglophone experts’ poor language skills often exclude them from contributing to the peer review in most influential journals [ 22 ]. Comments should be properly edited to convey messages in positive or neutral tones, express ideas of varying degrees of certainty, and present logical order of words, sentences, and paragraphs [ 23 , 24 ]. Consulting linguists on communication culture, passing advanced language courses, and honing commenting skills may increase the overall quality and appeal of the reviewer accomplishments [ 5 , 25 ].

Peer reviewer credits

Various crediting mechanisms have been proposed to motivate reviewers and maintain the integrity of science communication [ 26 ]. Annual reviewer acknowledgments are widely practised for naming manuscript evaluators and appreciating their scholarly contributions. Given the need to weigh reviewer contributions, some journal editors distinguish ‘elite’ reviewers with numerous evaluations and award those with timely and outstanding accomplishments [ 27 ]. Such targeted recognition ensures ethical soundness of the peer review and facilitates promotion of the best candidates for grant funding and academic job appointments [ 28 ].

Also, large publishers and learned societies issue certificates of excellence in reviewing which may include Continuing Professional Development (CPD) points [ 29 ]. Finally, an entirely new crediting mechanism is proposed to award bonus points to active reviewers who may collect, transfer, and use these points to discount gold open-access charges within the publisher consortia [ 30 ].

With the launch of Publons ( http://publons.com/ ) and its integration with Web of Science Group (Clarivate Analytics), reviewer recognition has become a matter of scientific prestige. Reviewers can now freely open their Publons accounts and record their contributions to online journals with Digital Object Identifiers (DOI). Journal editors, in turn, may generate official reviewer acknowledgments and encourage reviewers to forward them to Publons for building up individual reviewer and journal profiles. All published articles maintain e-links to their review records and post-publication promotion on social media, allowing the reviewers to continuously track expert evaluations and comments. A paid-up partnership is also available to journals and publishers for automatically transferring peer-review records to Publons upon mutually acceptable arrangements.

Listing reviewer accomplishments on an individual Publons profile showcases scholarly contributions of the account holder. The reviewer accomplishments placed next to the account holders’ own articles and editorial accomplishments point to the diversity of scholarly contributions. Researchers may establish links between their Publons and ORCID accounts to further benefit from complementary services of both platforms. Publons Academy ( https://publons.com/community/academy/ ) additionally offers an online training course to novice researchers who may improve their reviewing skills under the guidance of experienced mentors and journal editors. Finally, journal editors may conduct searches through the Publons platform to select the best reviewers across academic disciplines.

Peer review ethics

Prior to accepting reviewer invitations, scholars need to weigh a number of factors which may compromise their evaluations. First of all, they are required to accept the reviewer invitations if they are capable of timely submitting their comments. Peer review timelines depend on article type and vary widely across journals. The rules of transparent publishing necessitate recording manuscript submission and acceptance dates in article footnotes to inform readers of the evaluation speed and to help investigators in the event of multiple unethical submissions. Timely reviewer accomplishments often enable fast publication of valuable works with positive implications for healthcare. Unjustifiably long peer review, on the contrary, delays dissemination of influential reports and results in ethical misconduct, such as plagiarism of a manuscript under evaluation [ 31 ].

In the times of proliferation of open-access journals relying on article processing charges, unjustifiably short review may point to the absence of quality evaluation and apparently ‘predatory’ publishing practice [ 32 , 33 ]. Authors when choosing their target journals should take into account the peer review strategy and associated timelines to avoid substandard periodicals.

Reviewer primary interests (unbiased evaluation of manuscripts) may come into conflict with secondary interests (promotion of their own scholarly works), necessitating disclosures by filling in related parts in the online reviewer window or uploading the ICMJE conflict of interest forms. Biomedical reviewers, who are directly or indirectly supported by the pharmaceutical industry, may encounter conflicts while evaluating drug research. Such instances require explicit disclosures of conflicts and/or rejections of reviewer invitations.

Journal editors are obliged to employ mechanisms for disclosing reviewer financial and non-financial conflicts of interest to avoid processing of biased comments [ 34 ]. They should also cautiously process negative comments that oppose dissenting, but still valid, scientific ideas [ 35 ]. Reviewer conflicts that stem from academic activities in a competitive environment may introduce biases, resulting in unfair rejections of manuscripts with opposing concepts, results, and interpretations. The same academic conflicts may lead to coercive reviewer self-citations, forcing authors to incorporate suggested reviewer references or face negative feedback and an unjustified rejection [ 36 ]. Notably, several publisher investigations have demonstrated a global scale of such misconduct, involving some highly cited researchers and top scientific journals [ 37 ].

Fake peer review, an extreme example of conflict of interest, is another form of misconduct that has surfaced in the time of mass proliferation of gold open-access journals and publication of articles without quality checks [ 38 ]. Fake reviews are generated by manipulating authors and commercial editing agencies with full access to their own manuscripts and peer review evaluations in the journal editorial management systems. The sole aim of these reviews is to break the manuscript evaluation process and to pave the way for publication of pseudoscientific articles. Authors of these articles are often supported by funds intended for the growth of science in non-Anglophone countries [ 39 ]. Iranian and Chinese authors are often caught submitting fake reviews, resulting in mass retractions by large publishers [ 38 ]. Several suggestions have been made to overcome this issue, with assigning independent reviewers and requesting their ORCID IDs viewed as the most practical options [ 40 ].

Conclusions

The peer review process is regulated by publishers and editors, enforcing updated global editorial recommendations. Selecting the best reviewers and providing authors with constructive comments may improve the quality of published articles. Reviewers are selected in view of their professional backgrounds and skills in research reporting, statistics, ethics, and language. Quality reviewer comments attract superior submissions and add to the journal’s scientific prestige [ 41 ].

In the era of digitization and open science, various online tools and platforms are available to upgrade the peer review and credit experts for their scholarly contributions. With its links to the ORCID platform and social media channels, Publons now offers the optimal model for crediting and keeping track of the best and most active reviewers. Publons Academy additionally offers online training for novice researchers who may benefit from the experience of their mentoring editors. Overall, reviewer training in how to evaluate journal submissions and avoid related misconduct is an important process, which some indexed journals are experimenting with [ 42 ].

The timelines and rigour of the peer review may change during the current pandemic. However, journal editors should mobilize their resources to avoid publication of unchecked and misleading reports. Additional efforts are required to monitor published contents and encourage readers to post their comments on publishers’ online platforms (blogs) and other social media channels [ 43 , 44 ].

The authors declare no conflict of interest.

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