Community Detection in Dynamic Face-to-Face Interaction Networks:

A Louvain Algorithm Approach

Abstract

In this paper, we present a study that evaluates the suitability of the Louvain Algorithm in the context of face-to-face interaction networks. Traditional community detection methods face challenges in this context, necessitating specialized solutions. Our research addresses this gap, offering a systematic approach that aggregates individual game data and applies the Louvain Algorithm. The results demonstrate the algorithm’s effectiveness in consistently identifying the original 34 communities, demonstrating its relevance in face-to-face interaction networks.