基于JSCNM算法的微博网络社区发现研究

Research on the Microblogging Network Community Discovery Based on JSCNM Algorithm

提出一种将用户关系和用户兴趣两者融合的社区发现算法——JSCNM算法,然后利用JS距离公式计算用户兴趣相似度距离,使用相似度代替模块度对用户关系和用户兴趣双内聚处理,发现用户社区。最后通过爬取新浪微博4个数据集进行实验操作,并对照CNM算法和GN算法,结合社区评价标准模块度的大小,证明该算法能够更准确、合理地发现用户社区。

A kind of community discovery algorithm which was named JSCNM fused the relationship between user links and user interests was proposed. JS distance formula was used to calculate the user interest similarity distance, and the user community was discovered by using the similarity degree of relationship between user links and interests instead of modularity. Finally, through CNM and GN algorithm by using four experimental data set for operation and combined with modularity the community evaluation standard, JSCNM algorithm was proved to be better in finding more accurate and reasonable user communities.