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.
Highlights
User group in social network site (SNS) has been garnering increased attention in fields of topic related opinion expression and information sharing [1]
We propose a topic space oriented user group discovering scheme based on trust in social network, which is composed of three phases: topic space detection, interest evaluation, and user grouping based on trust chain
The main contributions of this work include (1) putting forward a topic space construction method based on topic relatedness clustering and impact evaluation, including influence degree and popularity degree evaluation; (2) setting up a trust chain model by taking user relation network topological information into account with a strength classification perspective; (3) presenting a user interest degree evaluation method which involves explicit and implicit interest degree calculation based on trust chain prediction; (4) proposing a topic space oriented user group discovering method
Summary
User group in social network site (SNS) has been garnering increased attention in fields of topic related opinion expression and information sharing [1]. The main contributions of this work include (1) putting forward a topic space construction method based on topic relatedness clustering and impact evaluation, including influence degree and popularity degree evaluation; (2) setting up a trust chain model by taking user relation network topological information into account with a strength classification perspective; (3) presenting a user interest degree evaluation method which involves explicit and implicit interest degree calculation based on trust chain prediction; (4) proposing a topic space oriented user group discovering method. Core users who have large explicit interest in topic space are grouped according to explicit interest evaluation and ordinary users who have implicit interest are further estimated based on trust chain in social network
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