Kerstin Nicolay, TU Kaiserslautern
A Parallel Method for Community Detection in Large Networks
The analysis of networks on extremely large data sets has become essential in recent research. One main interest is the detection of communities within the network, but common examples like the social network Facebook or the citation network of Wikipedia easily exist of over a billion nodes. The problem of optimizing the so called modularity (a measure for determining the quality of a community) is NP-hard, therefore the talk presents a heuristic but very fast approach of Blondel et al., the Louvain method, for finding communities in large networks. Furthermore, an analysis of a possible parallelization of the method is given.