Algorithm of Classifying Classes of Social Networks

Social Networks have become embedded in our daily life so much that we no longer realize it. But researches on the structures of networks are correspondingly fewer than their statistical properties, however, the studies of structural features are necessary and significant. Here we present an approach to study the structures of social networks based on Role-to-role Connectivity Profiles (RCP). We conduct experiments in some classical social networks, we find that the social networks with different functions exhibit obvious different profiles. Different from the classification of complex networks, social networks are divided into two distinct classes with strict judgement basis rather than vague judgement. In addition, according to the RCP, we can find important nodes in social networks, which is more significant than those with high degree. Through the use of the algorithm in social networks, we can thoroughly understand a social network by the comprehensive network classifications rather than only relying on community detection and other global properties.