Mining Social Graphs

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Explores community detection in graphs using modularity and edge betweenness.

Explores handling network data, including types of graphs, real-world network properties, and node importance measurement.

Explores link-based ranking, document classification, and graph mining techniques.

Delves into the complexities of information exchanges in the digital age.

Explores the computation of the modularity measure and betweenness centrality in graphs for community detection.

Explores graph coloring theory, spectral clustering, community detection, and network structures.

Covers the fundamentals of handling networks and centrality measures in graph theory.

Covers Facebook research on user analysis, motivations, identity, and privacy.

Delves into the Social Maximum Pilot Project in Lugano, focusing on transforming the decadent Pergasona Tower into a shared community space.

Explores graph traversal methods, spanning trees, and shortest paths using BFS and DFS.