Hello NPTEL Learners, In this article, you will find **NPTEL Social Networks Assignment 8 Week 8 Answers 2023**. All the Answers are provided below to help the students as a reference donâ€™t straight away look for the solutions, first try to solve the questions by yourself. If you find any difficulty, then look for the solutions.

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## NPTEL Social Networks Assignment 8 Answers 2023:

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#### Q.1. Consider the following graph G. What is the formula used to apply the principle of repeated improvement before normalisation to obtain convergence?

**A = P1 + P2 + P4, B = P1 + P3, C = P2 + P4, P1 = A + B, P2 = A + C, P3 = B, P4 = A + C**- A = P1 + P3 + P4, B = P1 + P3, C = P2 + P4, P1 = A + B, P2 = A + C, P3 = B, P4 = A + C
- A = P1 + P2 + P4, B = P1 + P3, C = P2 + P4, P1 = A + B, P2 = A + C, P3 = B, P4 = A + B
- A = P1 + P2 + P3, B = P1 + P3, C = P2 + P4, P1 = A + B, P2 = A + C, P3 = B, P4 = A + C

#### Q.2. For the given network H, what will happen after say 10 iterations of Page rank updates for the initial value of 1/3 for every node in the network

- The value at A steadily increases
- The value at C steadily decreases
**The value at C steadily increases**- The value at B steadily increases

#### Q.3. Consider a Graph H shown in figure 2. Which of the following is True for this graph?

- Doesnot converge
**Converges with all points in node C**- Converges zero points in node C
- Converges with maximum points in A and B

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#### Q.4. Pick out the matrix that represents the given graph J to view page rank as a matrix multiplication process:

**Answer: D**

Given a matrix M,Â M=[4352] and a vectorÂ V=[23] Apply M on V and normalise it to obtain the resultant vector,Â R=[ab] Note: Precision level of at least four decimal places to be considered for computation

#### Q.5.** **Enter the value of a ______________.

**Answer: 0.8**8

#### Q.6. Enter the value of b ______________.

**Answer:****0.455**

#### Q.7. Which of the following are TRUE for the Hubs and Authorities algorithm?

Statement I â€“ The Authority update rule states that for each page p, update auth(p) is the sum of the hub scores of all pages that point to it.

Statement II â€“ The Hub update rule states that for each page p, update hub(p) is the sum of the authority scores of all pages that it points to.

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Assume the shown pageranks for the given nodes at some point of time.Â

#### Q.8. Find the page rank score of web pages B in the next iteration:

**Answer: 6.5**

#### Q.9. Find the page rank score of web pages D in the next iteration:

**Answer: 5.5**

#### Q.10. What is the score value of authority(a) and hub(h) respectively for node 5 in the following figure after applying 1-step hub-authority computation (i.e. when k is 1)?Assume initial hub and authority of each node as 1.

#### Q.11. Two vectors V1 and V2 are added in the XY plane. Given that V1 is of a very high magnitude when compared to V2, then the resultant vector is

- same as V1
- independent of V2
**closer to the direction of V1**- closer to the direction of V2

#### Q.12. Which of the following is TRUE for a Markov Matrix?

Statement I â€“ The sum of elements in every column is same. Statement II â€“ Highest eigenvalue of a Markov matrix is 1.

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**Disclaimer**: This answer is provided by us only for discussion purpose if any answer will be getting wrong donâ€™t blame us. If any doubt or suggestions regarding any question kindly comment. The solution is provided byÂ **Chase2learn**. This tutorial is only for Discussion andÂ LearningÂ 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 Outcome:**

- Week 1:Â IntroductionÂ
- Week 2:Â Handling Real-world Network Datasets
- Week 3:Â Strength of Weak Ties
- Week 4:Â Strong and Weak Relationships (Continued) & HomophilyÂ
- Week 5:Â Homophily Continued and +Ve / -Ve RelationshipsÂ
- Week 6:Â Link AnalysisÂ
- Week 7:Â Cascading Behaviour in Networks
- Week 8:Â Link Analysis (Continued)Â
- Week 9:Â Power Laws and Rich-Get-Richer PhenomenaÂ
- Week 10:Â Power law (contd..) and EpidemicsÂ
- Week 11:Â Small World Phenomenon
- Week 12:Â 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.**

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