A topic space oriented user group discovering scheme in social network: A trust chain based interest measuring perspective

Abstract

Currently, user group has become an effective platform for information sharing and communicating among users in social network sites. In present work, we propose a single topic user group discovering scheme, which includes three phases: topic impact evaluation, interest degree measurement, and trust chain based discovering, to enable selecting influential topic and discovering users into a topic oriented group. Our main works include (1) an overview of proposed scheme and its related definitions; (2) topic space construction method based on topic relatedness clustering and its impact (influence degree and popularity degree) evaluation; (3) a trust chain model to take user relation network topological information into account with a strength classification perspective; (4) an interest degree (user explicit and implicit interest degree) evaluation method based on trust chain among users; and (5) a topic space oriented user group discovering method to group core users according to their explicit interest degrees and to predict ordinary users under implicit interest and user trust chain. Finally, experimental results are given to explain effectiveness and feasibility of our scheme.