nptel social networks assignment 4 answers 2023

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NPTEL Course "Social Networks" by Dr. S. R. S. Iyengar, IIT Ropar - Notes, Data sets and Programs

gokulkarthik/NPTEL-Social-Networks

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This repository contains the social networks course notes, network data sets and python programs for network analysis. Some of the surprising observations and beautiful discoveries achieved with Social Network Analysis are listed below.

• 6 degrees of separation: You can reach out to any person on this earth within an average of 6 hops. That means, "You know someone who knows someone who knows someone who knows someone who knows someone who knows Justin Beiber (or Angelina Jolie or literally anyone on this planet.)".
• The algorithm behind Google search: How does Google achieve such precise and valid search results? The underlying algorithm is fairly simple and relies totally on the network of web pages.
• How do you get your dream job: Not through your best friends but through your acquaintances to whom you talk relatively less frequently! Sounds counterintuitive.
• Link prediction: Can one predict who is going to be your next Facebook friend, or which product are you going to buy next on Flipkart, or which is the next movie you are going to watch on Netflix? Yes, it is possible.
• Viral Marketing: Want to make your new product sell out quickly? How do you determine the people to whom you should be giving the free samples? Does that even matter?
• Contagion: Not only information but happiness, obesity, altruism, depression all spread from person to person.

PRE-REQUISITES:

The course doesn’t assume any pre-requisites. We expect one has undergone a first course in basic programming.

COURSE INSTRUCTOR

Sudarshan Iyengar has a PhD from the Indian Institute of Science and is currently working as an assistant professor at IIT Ropar and has been teaching this course from the past 4 years.

COURSE LAYOUT

Week 1: Introduction to Graph Theory and Python

Week 2: Analyzing Online Social Network Datasets

Week 3: Power Law and Emergent Properties

Week 4: Strength of Weak Ties

Week 5: Homophily and Social Influence

Week 6: Structural Balance

Week 7: The Structure of the Web

Week 8: Link Analysis and Web Search

Week 9: Link Prediction

Week 10: Information Cascades

Week 11: Diffusion Behavior in Networks

Week 12: The Small World Phenomenon

Certification:

The criteria for certification in this course is different because of the online programming exam component. Please read the following carefully: Final score = Quiz score + Programming Assignment Score + Programming exam score + Proctored exam score Quiz score: 15% weightage with best 8 out of 12 Programming Assignment score: 10% weightage with best 4 out of 6 Online programming exam (unproctored): 10% weightage. Proctored exam (to be attended in person): 65% weightage

To pass the course and get a certificate: Final score >= 40/100 To get an Elite category of certificate: Final score >= 60/100 To get a gold medal stamp in the certificate: Final score >= 90/100

References:

https://onlinecourses.nptel.ac.in/noc18_cs02/preview

Contributors 2

• Jupyter Notebook 99.4%

Brokenprogrammers

Learning platform for programmers

NPTEL Social Networks Assignment 4 Answers 2023

Hello Learners, In this Post, you will find NPTEL Social Networks Assignment 4 Week 4 Answers 2023 . All the Answers are provided below to help the students as a reference don’t straight away look for the solutions.

NPTEL Social Networks Assignment 5 Answers Join Group👇

Note: First try to solve the questions by yourself. If you find any difficulty, then look for the solutions.

NPTEL Social Networks Assignment 4 Answers 2023:

We are updating answers soon Join Group for update: CLICK HERE

Q.1. Identify the type of Homophily in the following Linked inn recommendation: ”People with similar interests are following —-”

• Social Influence
• Membership closure
• Foci Closure

Q.2. Identify the network mechanism in play for the following transformation.

• Triadic closure
• Focal Closure
• Neighborhood overlap

Q.3. Two friends Raj and Nila have taken different courses according to their interests. Raj has completed 12 courses and Nila has completed 16 courses in all. There are 7 courses that Raj and Nila have taken up in common. What is the similarity measure for Raj and Nila?

Q.4. Suppose Manisha and Simran have a common friend with an independent probability p What is the probability that they donot have k common friends?

Q.5. what are the factors that influence the dynamics of friendships formation and behaviour of people in a network.

• Both Social Influence and Selection
• Neither Social Influence nor Selection

Q.6. In the fatman evolutionary model, what is the role of social foci?

Q.7. compute homophily for the given network., nptel social networks week 4 answers join group👇, q.8. what is the relationship that exists between the probability of any two persons(a and b) being friends with respect to the number of their common friends.

• exponential

Q.9. A network having inter-community edge density and intra-community edge sparsity will definitely exhibit

• Heterophily

Q.10. Assume there are 20 participants who have just enrolled for a workshop. Which of the following closure happen in this current state?

• Focal closure

NPTEL Social Networks Assignment 4 Answers Join Group👇

Disclaimer : This answer is provided by us only for discussion purpose if any answer will be getting wrong don’t blame us. If any doubt or suggestions regarding any question kindly comment. The solution is provided by  Brokenprogrammers . This tutorial is only for Discussion and Learning purpose.

About NPTEL Social Networks Course:

The world has become highly interconnected and hence more complex than ever before. We are surrounded by a multitude of networks in our daily life, for example, friendship networks, online social networks, world wide web, road networks etc. All these networks are today available online in the form of graphs which hold a whole lot of hidden information. They encompass surprising secrets which have been time and again revealed with the help of tools like graph theory, sociology, game theory etc. The study of these graphs and revelation of their properties with these tools have been termed as Social Network Analysis.

Course Layout:

• Week 1: Introduction 
• Week 2: Handling Real-world Network Datasets
• Week 3: Strength of Weak Ties
• Week 4: Strong and Weak Relationships (Continued) & Homophily 
• Week 5: Homophily Continued and +Ve / -Ve Relationships 
• Week 6: Link Analysis 
• Week 7: Cascading Behaviour in Networks
• Week 8: Link Analysis (Continued) 
• Week 9: Power Laws and Rich-Get-Richer Phenomena 
• Week 10: Power law (contd..) and Epidemics 
• Week 11: Small World Phenomenon
• Week 12: Pseudocore (How to go viral on web)

CRITERIA TO GET A CERTIFICATE :

Average assignment score = 25% of average of best 8 assignments out of the total 12 assignments given in the course. Exam score = 75% of the proctored certification exam score out of 100

Final score = Average assignment score + Exam score

YOU WILL BE ELIGIBLE FOR A CERTIFICATE ONLY IF AVERAGE ASSIGNMENT SCORE >=10/25 AND EXAM SCORE >= 30/75. If one of the 2 criteria is not met, you will not get the certificate even if the Final score >= 40/100.

If you have not registered for exam kindly register Through https://examform.nptel.ac.in/

By Brokenprogrammers

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NPTEL Social Networks Assignment 8 Answers 2023

NPTEL Social Networks Week 4 Assignment Answers 2024

1. “People tend to have links to others who are similar to them”. Identify this process that impacts the structure of Social Network.

• Social Influence
• Triadic Closure
• Betweenness

2. Given two authors are editing Wikipedia articles. Number of articles edited by both author A and author B is 10. The total number of articles edited by either of them is 18. Compute the similarity measure.

3. Dynamics of friendships formation and behaviour of people in a network is affected by

• Both Selection and Social Influence
• Neither Selection nor Social Influence

4. Suppose Hari and Joy have k common friends. Given that each common friend gives Hari and Joy an independent probability p of forming a link, what is the probability that there will exist a link between Hari and Joy?

• 1 − (1 − p) k

5. Ram and Raghu met joined a Yoga class.Their similarity measure was 0.005 at the time of joining. They became good friends on Day 3. What is the similarity measure right before they became friends?

6. Given the friendship network in a dance school, 5 girls represented by red nodes and 5 boys represented by green nodes. Find the Homophily of the network.

7. Which of the following conditions is ideal for a good community?

• ratio of intra-community edges to inter-community edge should be high
• ratio of intra-community edges to inter-community edge should be low
• ratio of intra-community edges to inter-community edge should be 1
• ratio of intra-community edges to inter-community edge should be 0

8. Identify the network mechanism in play for the following transformation.

• Structural hole
• Focal closure
• Membership closure

9. When calculating the homophily value, what range of values is expected when the network exhibits heterogeneity?

• less than 1
• greater than 1

10. Which phenomenon is represented in region B of the given graph?

• Focal Closure

Social Networks | NPTEL | Week 4 Assignment Solutions

This set of MCQ(multiple choice questions) focuses on the  Social Networks NPTEL Week 4 Assignment Solutions .

Course layout (Answers Link)

Answers COMING SOON! Kindly Wait!

Week 0: Assignment answers Week 1:  Introduction Week 2: Handling Real-world Network Datasets Week 3: Strength of Weak Ties Week 4: Strong and Weak Relationships (Continued) & Homophily  Week 5:  Homophily Continued and +Ve / -Ve Relationships Week 6: Link Analysis   Week 7:  Cascading Behaviour in Networks Week 8:  Link Analysis (Continued) Week 9:  Power Laws and Rich-Get-Richer Phenomena Week 10:  Power law (contd..) and Epidemics Week 11: Small World Phenomenon Week 12: Pseudocore (How to go viral on web)

NOTE:  You can check your answer immediately by clicking show answer button. This set of “ Social Networks NPTEL 2022 Week 4 Assignment Solution” contains 10 questions.

Now, start attempting the quiz.

Social Networks NPTEL 2022 Week 4 Assignment Solutions

Q1. If two people in a social network have a friend in common, then there is an increased likelihood that they will become friends themselves at some point in the future. The above principle is referred as

a) Triadic closure b) Foci closure c) Membership closure d) None of the above

Q2. Two friends Simran and Soujanya like different set of food items. The set of food items Simran and Soujanya like is denoted by Si and So, respectively. Si has 17 elements whereas So has 21 elements and there are 12 items which are liked by both Simran and Soujanya (Si∩So = 12). What is the  similarity measure  of Simran and Soujanya, with respect to food items.

a) 12/17 b) 12/21 c) 6/19 d) 6/13

Q3. Among the given two networks below, which network shows the better evidence of Homophily? (Nodes are divided into two types-represented by different colors)

a) Network A b) Network B c) Both exhibit equally d) Can’t say

Q4. Which phenomenon best describes the network evolution in Figure 2?

a) Homophily b) Triadic Closure c) Foci closure d) Membership closure

Q5. Dynamics of friendships formation and behaviour of people in a network is

a) Impacted by neither – selection and social influence. b) Impacted by both, selection as well as social influence. c) Impacted by selection but not social influence. d) Impacted by social influence but not selection.

Social Networks NPTEL Week 4 Assignment Solutions

Q6. Consider figures A, B and C in Figure 3 and choose the right kind of closure they represent ( Please note that the solid line represents the existing friendship and the dotted line represents the new friendship .):

a) A: Triadic closure, B: Membership closure, C: Focal closure b) A: Membership closure, B: Triadic closure, C: Focal closure c) A: Focal closure, B: Triadic closure, C: Membership closure d) A: Focal closure, B: Membership closure, C: Triadic closure

Q7. Homophily refers to the friendship between people

a) who have a common friend b) who have same ethnicity c) who are similar to each other d) who are dissimilar to each other

Q8. Suppose Monica and Chandler have kk common friends. Given that each common friend gives Monica and Chandler an independent probability pp of forming a link, what is the probability that there will exist a link between Monica and Chandler?

a) p k b) 1−(1−p)×k c) 1−(1−p) k d) pk

Social Networks NPTEL week 4 Assignment Solutions

Q9. Let G be a complete graph with n nodes. The total number of triangles possible in G is:

a) n 3 b) n(n−1)(n−2)/6 c) 3n d) None of the above

Q10. What will the output of the following two variables respectively (written in Python3): A = [1, 2, 3, 4] + [3, 4, 5, 6] S = [1, 2, 3, 4] – [3, 4, 5, 6]

a) [1, 2, 3, 4, 5, 6], [1, 2, 5, 6] b) [4, 6, 8, 10], [-2, -2, -2, -2] c) 28, -8 d) [1, 2, 3, 4, 3, 4, 5, 6], TypeError:unsupported operand type

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Course Name: Social Networks

• About Course
• Certificate Type
• Toppers list
• Registration

Course abstract

The network of friendships on Facebook, road connections, terrorist networks and disease spreading networks are today available as a graph G(V,E). Social Network Analysis involves discerning this graph data and making sense out of it. The course will revolve around the study of some well-known theories of social and information networks and their applications on real world datasets.

Course Instructor

Prof. Sudarshan Iyengar

Sudarshan Iyengar has a Ph.D. from the Indian Institute of Science and is currently working as an assistant professor at IIT Ropar and has been teaching this course from the past 5 years. Apart from this course, he has offered several other courses in IIT Ropar like Discrete Mathematics, Theory of Computation, Cryptography, Probability and Computing etc. His research interests include social networks, crowdscoured knowledge building and computational social sciences. His current research proects are "Predicting a Viral meme" (Yayati Gupta), "Understanding Crowdsourced Knowledge buidling" (Anamika Chhabra - Scientist), "Secure Computation" (Varsha Bhat) and "Network Sampling" (Akrati Saxena). After research, teaching makes the major component of his academic life. He enjoys experimenting with different teaching methodologies. He particularly enjoys traveling and giving talks on his research work apart from motivational talks of popsci genre.

Teaching Assistant(s)

 course duration : jul-oct 2018,   view course,  syllabus,  enrollment : 18-apr-2018 to 30-jun-2018,  exam registration : 25-jun-2018 to 18-sep-2018,  exam date : 28-oct-2018,   course statistics will be published shortly, certificate eligible, certified category count, successfully completed, participation.

Category : Successfully Completed

Category : Elite

Category : Gold

>=90 - Elite + Gold 60-89 - Elite 40-59 - Successfully Completed <40 - No Certificate

Final Score Calculation Logic

• Assignment Score = Average of best 8 out of 12 assignments.
• Final Score(Score on Certificate)= 75% of Exam Score + 25% of Assignment Score

DEEPENDRA BHUSHAN 95%

RADHARAMAN INSTITUTE OF TECHNOLOGY AND SCIENCE BHOPAL MADHYA PRADESH

RAMANUJAM S 88%

INFOSYS LTD

DEEPASREE VARMA P 87%

SCMS SCHOOL OF ENGINEERING & TECHNOLOGY

ABINRAJ K B 86%

SCHOOL OF ENGINEERING

R. ABHINAV 86%

INDIAN INSTITUTE OF TECHNOLOGY,TIRUPATI

SOBYASACHI CHATTERJEE 85%

RAMAKRISHNA MISSION RESIDENTIAL COLLEGE (AUTONOMOUS)

RODGE VIDYA SUDAMRAO 84%

INDIAN INSTITUTE OF TECHNOLOGY TIRUPATI

VIDHATHRI 84%

INDIAN INSTITUTE OF INFORMATION TECHNOLOGY, DESIGN AND MANUFACTURING, KANCHEEPURAM

GOWTHAMI CHERUKURI 84%

MANVI BREJA 83%

MANAV RACHNA UNIVERSITY

H.SUSMITHA 82%

KUPPAM ENGINEERING COLLEGE

KAVEL BARUAH 82%

TEZPUR UNIVERSITY

ANTARA ROY CHOUDHURY 81%

BMS COLLEGE OF ENGINEERING

VISALAKSHI M 81%

PSG COLLEGE OF TECHNOLOGY

TASHIA HASAN 81%

INTEGRAL UNIVERSITY

HARINI R 80%

SUBHRAJIT MITRA 80%

GOVERNMENT COLLEGE OF ENGINEERING AND TEXTILE TECHNOLOGY , SERAMPORE

SAMEENA FATHIMA.M 79%

ST.JOSEPHS COLLEGE OF ENGINEERING

LIFNA C S 78%

VES INSTITUTE OF TECHNOLOGY

KAMAL DAS 77%

ABHAY SINGH CHAUHAN 76%

VIT UNIVERSITY-VELLORE

ARAVINDH SEKAR C 76%

Enrollment Statistics

Total enrollment: 6808, assignment statistics, feedback videos.

Score Distribution Graph - Legend

Assignment score: distribution of average scores garnered by students per assignment., exam score : distribution of the final exam score of students., final score : distribution of the combined score of assignments and final exam, based on the score logic..

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Week 1:  What is Online Social Networks, data collection from social networks, challenges, opportunities, and pitfalls in online social networks, APIs  Week 2:  Collecting data from Online Social Media.  Week 3:  Trust, credibility, and reputations in social systems Week 4:  Trust, credibility, and reputations in social systems Week 5:  Online social Media and Policing  Week 6:  Information privacy disclosure, revelation and its effects in OSM and online social networks Week 7:  Phishing in OSM & Identifying fraudulent entities in online social networks Week 8:  Refresher for all topics  Week 9 to 12: Research paper discussion

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Social Networks | Week 7

Session: JULY-DEC 2023

Course Name: Social Networks

Course Link: Click Here

These are Nptel Social Networks Week 7 Assignment 7 Answers

Q1. A cascade cannot be complete in a network with threshold of adoption = q, if there exist a cluster with density lesser than q greater tan q lesser than (1 – q) greater than (1 – q)

Answer: greater than (1 – q)

Q2. Let ‘x’ be a node in a graph. Suppose that a ‘p’ fraction of the neighbors of ‘x’ have behavior A, and a (1 – p) fraction have behavior B; that is, if ‘x’ has ‘d’ neighbors, then pd adopt A and (1- p)d adopt B, as shown in the following Figure. Behavior A has a payoff of ‘a’ and behavior B has a payoff of ‘b’. Then A is a better choice for ‘x’ if p ≥ a/b p ≥ b/a p ≥ a/(a + b) p ≥ b/(a + b)

Answer: p ≥ b/(a + b)

Q3. Find the cluster density of the blue color nodes shown in the given figure 14. 1/2 2/3 3/4 3/5

Answer: 3/5

Q4. Which of the following are valid factors for influence diffusion? Payoff Key people Both Payoff and key people Neither Payoff nor key people

Answer: Both Payoff and key people

Q5. Consider the basic coordination based game theoretical model for cascading behavior. The payoffs associated with behaviours ‘A’ and ‘B’ are a and b respectively. Consider two friends x and y adopting behaviours ‘A’ and ‘B’ respectively. Assuming that x and y have no other friends than each other, the total payoff which they receive is ab a + b a/b b/(a + b)

Answer: a + b

Q6. Given a network as shown in the following Figure, assume that initially every node in this network has adopted behavior B. Next, a new behavior A is introduced in the network and the nodes 1 and 3 are the initial adopters of this behavior A, i.e., nodes 1 and 3 now have adopted behavior A and the rest of the nodes have adopted behavior B. The payoff associated with A is a = 3 and the payoff associated with B is b = 2. After the introduction of this new behavior A in the network, all the nodes will start weighing their options and might change their behavior. This leads to a cascade in the network. When the cascade ends, which all are the nodes who have adopted the behavior A. 1, 3, 2 1, 3, 2, 4 1, 3, 2, 4, 5 1, 3

Answer: 1, 3, 2, 4

Q7. Let us consider a model for collective action shown in Figure 16, where the intrinsic threshold is given for every node. Which of the following statements is INCORRECT for this case? u will go for a protest as it has two neighbors and its threshold is two v will not go for a protest because w has a threshold of 4 and there are only two other nodes in the network w will not go for a protest because its threshold is 4 and there are only two neighbors all three nodes will go for a protest as the average threshold is 3 and there are three nodes in the network

Answer: A, D

Q8. Given a node X having 10 friends/neighbors. 3 of its neighbors have decided to adopt the behavior/action A having a payoff of 12 while 7 of its friends have adopted the action B yielding a payoff of 9. What is (i) the payoff that X gets from its friends who have adopted the action A, (ii) the payoff that X gets from its friends who have adopted B, (iii) The final action/behavior adopted by X? (i) 36 ,(ii) 63, (iii) B (i) 63 ,(ii) 36, (iii) B (i) 36 ,(ii) 63, (iii) A (i) 63 ,(ii) 36, (iii) A

Answer: (i) 36 ,(ii) 63, (iii) B

Q9. Consider the social network in the Figure 17, and again let’s suppose that in the A-B coordination game. Initially, all nodes have adopted B. There are two initial adopters node 7 and 8 for A. we have a payoff of a = 3 and b = 2, what is the threshold for any node to switch from B to A? 2/3 3/2 2/5 3/5

Answer: 2/5

Q10. For the A-B coordination Game mentioned in Question 9, What are the nodes that have adopted action A after the next three steps? nodes 5 to 10 nodes 4 to 10 nodes 4 to 17 all nodes 1 to 17

Answer: nodes 4 to 10

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Session: JAN-APR 2023

Q1. If the payoff of playing a game and working out in the Gym is given as 0.6 and 0.4 respectively. Four of your friends decides to play and five of them decide to work out. Which one should you pick? a. Playing a Game b. Work out in the Gym c. Data insufficient to decide d. None

Answer: a. Playing a Game

Q2. Which of the following technique helps to identify the important node in the network so that the idea spreads to the entire network very fast? a. Community detection b. Page ranking c. Viral marketing d. Embeddedness

Answer: c. Viral marketing

Q3. Consider a network with adoption threshold ‘q’. A cascade cannot be complete in this network if there exists a cluster of density a. less than q b. less than 1-q c. greater than q d. greater than 1-q

Answer: b. less than 1-q

Q4. Find the density of Community c1, c2 and c3 for the following network.

a. 5/6, 7/10, 8/10 b. 5/30, 7/30, 8/30 c. 4/6, 6/10, 7/10 d. 4/30, 7/30, 8/30

Answer: a. 5/6, 7/10, 8/10

Q5. Consider the graph G in Figure 1, which one of the communities is difficult for an idea to be injected? a. c1 b. c2 c. c3 d. None

Answer: a. c1

Q6. Any cascade on a complete network with only one seed node a. will always be complete b. will always be incomplete c. is difficult to occur d. Can’t say – insufficient information

Answer: d. Can’t say – insufficient information

Q7. What is the cluster density of the each of the four node cluster?

a. 1/3 b. 2/3 c. 3/4 d. 4/3

Answer: b. 2/3

Q8. Consider the network given in the following figure. Initially all the nodes in the network adopt an idea Y. Nodes A nd B adopt a new idea X in the network. The payoff for X is 4 and Y is 1. This leads to a cascade in the network. What are all the nodes that have adopted the behavior A when the cascade ends?

a. A, B, C b. A, B, C, D c. A, B, C, D, E d. A, B, C, D, E, F e. A, B, C, D, E, F, G, H, I, J

Answer: b. A, B, C, D

Q9. Consider a network where all of its nodes have adopted an idea A. Which of the following efforts can be a valid attempt to create a complete cascade of a new idea B in such a network. Select all that is applicable. a. Increase the payoff for the new idea b. Identify key people in the network to inject the idea c. Increase the payoff for idea A d. Identify the cluster with density q

Answer: a, b

Q10. Given the network K, assume a new idea has been adopted by the nodes, 0, 1, 2, 3, 4, and 5. How do you ensure that the new idea diffuses into the cluster marked by red dotted lines?

a. by diffusing it to the nodes 6 and 12 b. by identifying the correct set of nodes from outside the cluster. c. Both d. Cascade is incomplete and it cannot enter the cluster

Answer: d. Cascade is incomplete and it cannot enter the cluster

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