NPTEL Social Networks Assignment 3 Answers 2023

Hello Learners, In this Post, you will find NPTEL Social Networks Assignment 3 Week 3 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 4 Answers Join Group👇

CLICK HERE

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

COURSE NAMEANSWER
NPTEL Social Networks Assignment 1 AnswersClick Here
NPTEL Social Networks Assignment 2 AnswersClick Here
NPTEL Social Networks Assignment 3 AnswersClick Here
NPTEL Social Networks Assignment 4 AnswersClick Here
NPTEL Social Networks Assignment 5 AnswersClick Here
NPTEL Social Networks Assignment 6 AnswersClick Here
NPTEL Social Networks Assignment 7 AnswersClick Here
NPTEL Social Networks Assignment 8 AnswersClick Here
NPTEL Social Networks Assignment 9 AnswersClick Here
NPTEL Social Networks Assignment 10 AnswersClick Here
NPTEL Social Networks Assignment 11 AnswersClick Here
NPTEL Social Networks Assignment 12 AnswersClick Here
NPTEL Social Networks Assignment 3 Answers 2023
NPTEL Social Networks Assignment 3 Answers 2023

NPTEL Social Networks Assignment 3 Answers 2023:

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

Q.1. Which of the following algorithm is used to detect communities in a network?

  • Girvan Newman
  • Page Rank
  • Hits
  • Both Girvan Newman and Page Rank

Q.2. Identify the mechanism that ensures 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.

  • Social Capital
  • Structural hole
  • Triadic closure
  • Neighborhood overlap

Q.3. Which of the following is True for the edge AB in Graph H?

I. It is a strong tie
II. It is a local bridge
III. It is a weak tie

  • Only I
  • Both I and II
  • Both II and III
  • I, II and III
NPTEL Social Networks Assignment 4 Answers Join Group👇

Q.4. Compute the embeddedness of the edge AB in the graph H in Figure 1.

  • 0
  • 1
  • 3
  • 4

Q.5. Find the Neighborhood overlap of of the edge connecting V0 and V2 in the graph P. in Figure 2

  • 3/5
  • 3/4
  • 1/4
  • 1

Q.6. Consider a large social network where we have two communities that are connected by only through two nodes P and Q. Apart from being a weak tie, this also exhibits a property called

  • Social Capital
  • Structural hole
  • Triadic closure
  • Neighborhood overlap
  • Closure
  • less diameter
  • High density
  • Brokerage
NPTEL Social Networks Week 3 Answers Join Group👇
CLICK HERE

Q.8. 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

Q.9. Pick out the statement that best describes betweenness centrality.

  • All the shortest paths between the given node and the highest degree node.
  • All the longest paths between the given node and the highest degree node.
  • All the shortest paths that pass through the given node.
  • All the longest paths that pass through the given node.

Q.10. While implementing the Girvan Newman algorithm on a certain graph G , you observe that edge E1 gets removed after edge E2 . What can you comment about them?

  • E1 has higher betweenness than E2
  • E2 has higher betweenness than E1
  • E2 has higher embeddedness than E1
  • E1 has higher embeddedness than E2
NPTEL Social Networks Assignment 3 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/

Leave a Reply

Your email address will not be published. Required fields are marked *