基于模体的社会网络特征分析

Using Motif to Characterize and Analyze Mesoscopic Features of Social Networks

模体是存在于网络中的重要介观结构,模体发现是研究社会网络结构的重要手段,通过模体存在性的研究可以更好地理解社会网络的演化规律。基于Rand-ESU方法研究不同类型网络的模体特征。实验结果表明:在社会网络中节点不但具有与度大节点相连的倾向,也具有以更大概率形成"三元闭包"的社区特征;占据"结构洞"的节点数量少但是在信息传播过程中起关键作用。因此可以认为社会网络的结构演化是由"优先连接"和"三元闭包"共同驱动的。

Motif is an important mesoscopic structure which exists in networks. Motif discovery is a key problem in data analysis of social networks. By studying the existence of motif in social networks topology structure,the evolution of networks can be understood better. The Rand-ESU algorithm was used in motif detection and motif features analysis. The difference of motifs features in social networks,power networks and Internet was compared and analyzed. The experimental result shows that social networks have greater probabilities to form the structure of ＂triadic closure＂. They have stronger community features and bigger clustering coefficients. And,nodes also have a tendency to connect with the hubs nodes. We also find that although the number of nodes occupy ＂structural holes＂is less,but it plays a key role in the information propagation. Through research an important conclusions can be drawled： ＂preferential attachment＂and ＂triadic closure＂are the reasons for driving network evolution.