Détection des communautés par le PageRank

Abstract

The detection of communities in networks plays a crucial role in understanding their structures. Applying pagerank to the task of community detection in complex networks can yield good results. In this thesis, we propose a new approach to community detection based on the most influential nodes, initialized using their pageranks, and then cluste- ring them. Our approach is effective, simple, and easy to implement. We compared our algorithm with some state-of-the-art algorithms on synthetic and real networks, using evaluation measures such as Modularity Q and Conductance, and obtained acceptable results.