PaNDEMON and P2PDEMON, parallel and distributed community detection algorithms
One of the most important problems in the field of social network analysis, and one of the most discussed ones, is community detection, aimed at clustering the nodes on the basis of their social relationships. Community detection is relevant in various fields, including: recommendation systems, link prediction and suggestion, epidemic spreading and information diffusion, sybil detection. In this project, we analyze various ego-based community detection algorithms and propose some new ones. In particular, PaNDEMON and P2PDEMON are new ego-based community detection algorithms, to address parallelism and distribution of P2P social networks.