# Social Networks | Week 9

**Course Name: Social Networks**

**Course Link: Click Here**

**These are Nptel Social Networks Week 9 Assignment 9 Answers**

**These are Nptel Social Networks Week 9 Assignment 9 Answers****Q1. Given set E = 1, 2, 3, …, 14,15. We pick a value a1 uniformly at random from this set E. Next, we pick another value a2, again uniformly at random from this set E. Similarly we pick 13 more values, a3, a4, ……, a15 (a total of 15 numbers are picked). Look at the sum S = a1 + a2 + …. + a15. Which of the following sets define the range from which the sum S can have values from?**

a. [15, 16, .., 225]

b. [15, 16, .., 150]

c. [15, 16, .., 250]

d. [1, 16, .., 225]

**Answer: a. [15, 16, .., 225]**

**Q2. Which of the following describes the distribution of marks among the students in a class room?**

a. Plot the percentage of students along the X axis and marks on the Y axis

b. Plot the student id along the X axis and the marks on the Y axis

c. Plot the marks along the X axis and the percentage of students on the Y axis

d. Plot the marks along the X axis and the student id on the Y axis

**Answer: c. Plot the marks along the X axis and the percentage of students on the Y axis**

**These are Nptel Social Networks Week 9 Assignment 9 Answers**

**Q3. Which of the following are real world examples of power law distribution?**

a. IQ of students

b. Birth weight

c. SAT scores

d. WWW graph

**Answer: d. WWW graph**

**These are Nptel Social Networks Week 9 Assignment 9 Answers**

**Q4. Identify all the invalid statements for Power law distribution.**

a. The characteristic equation for power law is 1/ek

b. power law degree distribution come by in real world networks because of preferential attachment

c. power law degree distribution come by in real world networks because of random attachment

d. The characteristic equation for power law is 1/ka where a is a constant

**Answer: a, c**

**Q5. Consider we have a network of nodes. How does the new incoming node select a node for preferential attachment?**

a. Node with maximum number of friends

b. Node with minimum number of friends

c. Node with high clustering coefficient

d. Node with high embeddedness

**Answer: a. Node with maximum number of friends**

**Q6. Given a network being generated by ‘rich get richer’ phenomenon. Figure 1 shows the snapshot of the network at time t. A new node ‘u’ enters the network at time t + 1 and makes an edge with one of the existing nodes. What is the node that has high probability to form an edge with the new node ‘u’?**

A

B

C

D

E

**Answer: C**

**These are Nptel Social Networks Week 9 Assignment 9 Answers**

**Q7. Given the network ‘C’ of five participants in a competition, a new student ‘F’ joins the team. What is the probability that the new student make friends with A or C or D?**

a. 3/10

b. 2/10

c. 2/10

d. 7/10

**Answer: a. 3/10**

**Q8. From the previous example in Figure 2 Network C, F became friends with A.What is the probability that a new incoming student H, makes friends with F?**

a. 1/12

b. 2/11

c. 1/11

d. 2/12

**Answer: c. 1/11**

**These are Nptel Social Networks Week 9 Assignment 9 Answers**

**Q9. For the same Figure 2 Network C, after the addition of node F, assume that a new node G has entered and made friends with A, C and D. What is the probability that any new node I makes friendship with G?**

a. 3/14

b. 3/10

c. 3/18

d. 3/17

**Answer: a. 3/14**

**Q10. In a random graph with 500 nodes and edges between any two nodes with a probability of 0.3, where can one expect the peak of the degree-distribution graph?**

a. 500

b. 250

c. 100

d. 150

**Answer: d. 150**

**These are Nptel Social Networks Week 9 Assignment 9 Answers**

**These are Nptel Social Networks Week 9 Assignment 9 Answers**

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