Résumé:
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.
