All MCQs

Communities represent mesoscale structure in which members interact more strongly with one another. Different algorithms formalize this intuitive definition in different ways.

Homophily captures the pattern that people with shared attributes or interests are often more likely to connect. It can shape observed communities and information flow.

Two users sharing many contacts occupy overlapping local social contexts. This signal is often used in link prediction, though it does not guarantee a connection.

One hop means traversing a single edge from the focal vertex. The resulting vertices are its immediate neighbors.

The coefficient compares actual edges among a vertex’s neighbors with the number that could exist. It captures the local tendency for friend-of-a-friend triangles.

Density compares observed connections with the maximum possible for the graph type and vertex count. A dense network has many of its possible edges present.

Vertices in one connected component can reach one another through one or more edges. No additional outside vertex can be added while preserving that property.

Among all possible paths, the shortest path uses the fewest edges in an unweighted graph. Its length measures graph separation between the vertices.

A path describes a route through the graph in which consecutive vertices share an edge. Directed paths must also follow edge direction.

Out-degree counts directed edges beginning at the vertex. In this setting, it measures how many accounts the user follows.

In-degree counts directed edges whose arrow points into the vertex. For a follower network, these edges commonly represent people following that user.

Degree counts how many direct connections a vertex has in an undirected network. It is a basic measure of local connectivity.