基于社群发掘构建在线社交网络的高层架构

Constructing high-level architecture of online social network through community detection

针对在线社交网络的巨大规模和复杂结构造成的网络分析困难问题,提出建立简明的在线社交网络的高层架构。定义在线社交网络高层架构由社群、链接中心及其它们之间的关联关系组成,提出一种基于社群发掘的在线社交网络高层架构构建方法。通过建立定量属性图来表达在线社交网络,综合利用节点和边的属性进行社群发掘。基于社群发掘结果辨识连接中心,生成社群和连接中心之间的关联关系,从而构建起在线社交网络的高层架构,实现对复杂在线社交网络的高层次的简明表达。将该方法用于建立一个商业电子公告板(BBS)在线社交网络的高层架构,在关联强度和社群尺度分别为0.5和3时可获得良好的社群发掘结果,建立的高层架构与实际情况比较一致。

The online social network poses severe challenges because of its large size and complex structure. It is meaningful to construct a concise high-level architecture of the online social network. The concise high-level architecture was composed of the communities, the hub nodes and the relationships between them. The original online social network was represented by a new representation named quantitative attribute graph, and a new method was proposed to construct the concise high-level architecture of the online social network. The communities were detected by using the attributes of the nodes and edges in combination, then the hub nodes were identified based on the found communities, and the relationships between the communities and hub nodes were reproduced. The new method was used to construct the concise high-level architecture of a large online social network extracted from a practical business Bulletin Board System （BBS）. The experimental results show that the proposed method has a good performance when the relationship strength and the community size are set as 0.5 and 3 respectively.