Modeling bimodal social networks subject to recommendation

Abstract

This paper describes modeling of social networks subject to recommendation. Cold Start User-Item Model (CSUIM) of bipartite graph is considered, which simulates bipartite graph growth based on several parameters. An algorithm is proposed to compute parameters of this model from real graph data so that real graph and its model have similar graph metrics.