NPTEL Social Networks Week 2 Assignment Answers 2025
1. A graph has a diameter of 1. Which of the following statements must be true?
- The graph is a complete graph.
- All nodes in the graph are directly connected to every other node.
- The graph contains the maximum possible number of edges for its number of nodes.
- The graph is sparse with relatively fewer edges compared to nodes.
- Adding or removing an edge cannot change its diameter.
Answer :- For Answers Click Here
2. In the Web Graph model, what do the nodes and edges represent?
- Nodes are web pages, and edges are hyperlinks between them.
- Nodes are servers, and edges are data transfer rates.
- Nodes are users, and edges are user interactions.
- Nodes are hashtags, and edges are co-occurrence frequencies.
Answer :-
3. A dataset represents a multigraph (a graph where multiple edges are allowed between two nodes). Which method in NetworkX allows you to load such a graph from an edge list file?
- read_multiedgelist()
- read_edgelist() with create_using=nx.MultiGraph()
- read_gml()
- read_multigraph()
Answer :-
4. Consider the following GML representation of a directed graph:
Which of the following correctly interprets the structure and properties of the graph described by the GML code?
- The graph is undirected, with two nodes labeled “A” and “B” connected by two edges with weights 5 and 3, respectively.
- The graph is directed, with node “A” pointing to node “B” with a weight of 5, and node “B” pointing back to node “A” with a weight of 3.
- The graph is directed, with node “A” pointing to node “B” with a weight of 3, and node “B” pointing to node “A” with a weight of 5.
- The graph is directed and contains a self-loop at node “A” with a weight of 5, and another self-loop at node “B” with a weight of 3.
Answer :-
5. Consider the following characteristics of different social network dataset formats. Which of the following statements is true about these formats?
- Adjacency Matrix is most efficient for storing sparse graphs because it requires minimal space for large graphs with few edges.
- Edge List format is not ideal for storing sparse graphs as it does not require extra space to store non-existing edges between nodes.
- Adjacency List is space-efficient for sparse graphs and allows for fast traversal of neighbors, making it suitable for networks with relatively few edges compared to nodes.
- Gephi File format is designed for large-scale networks and is not ideal for visualizing or analyzing graphs with edge weights or node attributes.
Answer :-
6. Pajek datasets are usually available in which of the following format?
- .csv
- .net
- .txt
- .tar
Answer :- For Answers Click Here
7. Which NetworkX function would you use to visualize the degree distribution of a graph?
- nx.degree_histogram(G)
- nx.closeness_centrality(G)
- nx.shortest_path_length(G)
- nx.eigenvector_centrality(G)
Answer :-
8. In Gephi, which metric would you compute to determine the connectivity between communities in a graph?
- Modularity
- Degree centrality
- Closeness centrality
- Betweenness centrality
Answer :-
9. In the context of graph theory, what is the critical threshold for the emergence of a giant connected component in a random graph?
- When the number of edges equals the number of nodes.
- When the average degree is 1.
- When the clustering coefficient reaches 1.
- When the network diameter becomes constant.
Answer :-
10. In a random graph G(n,p), when does a giant connected component typically emerge?
- When the edge probability p is very small.
- When the edge probability p is large enough to connect most nodes.
- When the number of nodes n is very large.
- When the graph has no isolated nodes.
Answer :- For Answers Click Here
