Poster
in
Workshop: Symmetry and Geometry in Neural Representations (NeurReps)
Mixed-Membership Community Detection via Line Graph Curvature
Yu Tian · Zachary Lubberts · Melanie Weber
Keywords: [ Mixed-membership community detection ] [ Ollivier-Ricci curvature ] [ Curvature-based Network Analysis ] [ Line Graph ]
Community detection is a classical method for understanding the structure of relationaldata. In this paper, we study the problem of identifying mixed-membership communitystructure. We argue that it is beneficial to perform this task on the line graph, which canbe constructed from an input graph by encoding the relationship between its edges. Here,we propose a curvature-based algorithm for mixed-membership community detection onthe line graph. Our algorithm implements a discrete Ricci curvature flow under which theedge weights of a graph evolve to reveal its community structure. We demonstrate theperformance of our approach in a series of benchmark experiments.