1. In a growing scale-free network, the probability that a new node connects to an existing node i is proportional to:
a) The square of the node’s current degree b) The reciprocal of the node’s current degree c) The logarithm of the node’s current degree d) The node’s current degree
2. In a preferential attachment model, what happens to the degree distribution as the network grows?
a) It follows a power-law distribution where few nodes have extremely high degrees. b) It approaches a normal distribution with most nodes having a similar degree. c) The network stabilizes with a fixed number of high-degree nodes. d) The degree distribution converges to a Poisson distribution.
3. In a random network, disease spread follows a classic percolation model. What additional factor makes epidemic spreading in a scale-free network more dangerous?
a) The presence of hubs that accelerate disease transmission. b) The clustering coefficient is higher, preventing transmission. c) Scale-free networks have a fixed diameter, limiting the spread. d) The degree distribution follows a Poisson distribution, reducing risk.
4. How does network structure affect the basic reproductive number (R0) of an epidemic?
a) In scale-free networks, (R0) is highly variable due to heterogeneous degree distribution. b) In random networks, (R0) is always greater than 1. c) In lattice-based networks, (R0) is exponentially high due to structured connectivity. d) Network structure has no effect on (R0).
Nptel Social Networks Week 10 Assignment 10 Answers
5. If an epidemic spreads faster than expected in a scale-free network, which intervention strategy is most effective?
a) Randomly vaccinating 50% of the population b) Isolating nodes with high clustering coefficient c) Targeted vaccination of high-degree nodes (hubs) d) Reducing the number of edges per node uniformly
6. The key reason why an SIR model behaves differently from an SIS model in networks is:
a) SIR models assume no reinfection, while SIS allows reinfection. b) SIS models lead to disease eradication, while SIR does not. c) SIR models require a fixed network topology, while SIS does not. d) In SIS models, the disease persists indefinitely, even if R0 < 1.
7. In the percolation model of epidemics, what does the percolation threshold represent?
a) The fraction of removed edges needed to prevent an epidemic. b) The time taken for the entire network to be infected. c) The fraction of nodes vaccinated before herd immunity occurs. d) The degree distribution required to sustain an epidemic.
8. When analyzing network robustness, which strategy best describes the difference between random node failure and targeted node attack?
a) Scale-free networks remain robust under random failures but collapse under targeted attacks. b) Scale-free networks collapse equally under random and targeted attacks. c) Removing low-degree nodes has the same impact as removing hubs. d) Random node failures and targeted attacks follow identical percolation dynamics.
9. In a simple branching process model of disease spread, what is the probability that an epidemic dies out after a few generations?
a) Pextinction=1R0P_{extinction} = \frac{1}{R0} if R0>1R0 > 1 b) Pextinction=1−1R0P_{extinction} = 1 – \frac{1}{R0} if R0>1R0 > 1 c) Pextinction=e−R0P_{extinction} = e^{-R0} for all values of R0R0 d) Epidemics always spread indefinitely in branching models
