Dynamic Community Detection in Weighted Graph Stream

Networks are always complex and evolving, but dynamic community detection and clustering analysis is a challenge for existing methodologies or algorithms which only work for the static version. The project intends to study the latest literature on dynamic clustering networks and evaluate three different algorithms, which are Dynamo, Clustering Activation Network, and LWEP, on clustering quality. Several experiments about clustering quality testing are carried out to compare the performances of these three algorithms through different given real-world datasets. This paper summarizes and evaluates the experiment results of the project.