基于用户相似度度量的有效社区Leader选举方法

社交网络社区Leader 选举,即识别社区内影响力最大用户,是社交网络结构分析重要任务之一,在识别意见领袖、增进社区融合等方面具有重要的理论和应用研究价值.传统的社区Leader 选举技术如UserRank和PeopleRank,主要基于社交网络链接分析实现,忽略了用户本身属性的相似度度量.因此得到的社区Leader不能有效保证其社区代表性.本文提出了一种新的用户关系建模方法,将传统的链接分析和用户属性相似度度量融合,有效识别具有代表性的高影响力用户.实验结果表明,提出的方法不仅可以选举出社区内部具有代表性的高影响力Leader 用户,还可以通过社区Leader 选举使得社区内其他用户的查询效率得到有效提高.

An efficient user similarity metric based community leader electing approach

The election of community leader, which is used to select the high-impact user in the social community, is one of theimportant structural analysis based tasks in social network.It has important theoretical and practical value in both identifying opinionleaders and promoting community integration. However, most of the proposed approaches such as UserRank and PageRank, neglectingthe important attributes similarity between different users, are implemented based on the linking analysis in social network.In this paper, a new user relationship model is proposed by efficiently combining the traditional linking analysis based on graphstructure and similarity metric based on user attributes. Experimental results demonstrate that the high-impact user in the socialcommunity can be selected and in turn be used to improve other users＇ query efficiency.