A Social Network Model Based on Topology Vision

Hsiao, Ping-Nan

There are many researchers proposed social network models in recent years, and most of them focus on clustering coefficient property of a small-world network and power law degree distribution of a scale-free property. In social network topology, we observed the network is consisted of many nodes with small connectivity and a few high-degree nodes. In the small connectivity part, there are many nodes which have only one degree. Most of past social network models can not generate this part. In this paper, we proposed a social network model based on topology vision and with tunable high hub connectivity. At the same time, we suggested a new characteristic of social network, condensed clustering coefficient, to replace the original clustering coefficient. Finally, this study also includes the analysis of real social network data.