  With the rapid development of Internet technology, online social networks
(OSNs) have got fast development and become increasingly popular. Meanwhile,
the research works across multiple social networks attract more and more
attention from researchers, and community detection is an important one across
OSNs for online security problems, such as the user behavior analysis and
abnormal community discovery. In this paper, a community detection method is
proposed across multiple social networks based on overlapping users. First, the
concept of overlapping users is defined, then an algorithm CMN NMF is designed
to discover the stub communities from overlapping users based on the social
relevance. After that, we extend each stub community in different social
networks by adding the users with strong similarity, and in the end different
communities are excavated out across networks. Experimental results show the
advantage on effectiveness of our method over other methods under real data
sets.
