NPTEL Social Networks Week 3 Assignment Answers 2025
1. Which of the following best explains the concept of “strength of weak ties” in social networks?
- Weak ties are not important in social networks.
- Weak ties connect different groups, facilitating the flow of new information.
- Weak ties are more trustworthy than strong ties.
- Weak ties only exist within closely connected groups.
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2. In a social network, a triad refers to:
- A group of three nodes where all are connected.
- A set of three nodes connected by a single edge.
- A group of three nodes with no connections.
- A set of three nodes, with exactly two connected.
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3. Neighbourhood overlap in a graph is best described as:
- The number of edges between two nodes.
- The number of common neighbors two nodes share.
- The degree of a node.
- The shortest path between two nodes.
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4. In the context of social network analysis, a bridge is:
- An edge that connects two components.
- An isolated node in the graph.
- A node that connects two communities.
- An edge that connects two nodes with no common neighbors.
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5. A local bridge is an edge that:
- Connects two nodes with high degree.
- Has the highest betweenness centrality in the graph.
- Connects two nodes that have few or no other connections between them.
- Connects two nodes that belong to the same community.
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6. In the context of social networks, embeddedness refers to:
- The number of connections a node has.
- The degree to which a relationship is supported by a network of other relationships.
- The isolation of a node in the network.
- The shortest path between two nodes in the graph.
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7. A structural hole in a network refers to:
- A complete graph with no isolated nodes.
- A gap between two groups that are not directly connected.
- A node with the highest centrality in the network.
- A cluster of nodes that are all connected to each other.
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8. Social capital in a network context refers to:
- The total number of edges in the graph.
- The sum of all the connections a node has.
- The resources available to an individual through their social connections.
- The average degree of the nodes in the network.
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9. In the brute-force method for community detection, the number of possible ways to divide a graph with nn nodes into two distinct communities is:
- 2n
- 2n−1
- 2n−2
- 2n2
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10. The Girvan-Newman algorithm for community detection works by:
- Removing edges with the lowest betweenness centrality.
- Removing edges with the highest degree.
- Removing edges with the highest betweenness centrality.
- Randomly removing edges until the network splits into communities.
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