Measuring Domain-Specific User Influence in Microblogs: An Actor-Network Theory Based Approach

As Sina Weibo is becoming one of the most popular online social networking platforms in China, there is growing need in extracting knowledge and analyzing user behavior out of it. Influential user discovery has been quickly identified as an important application for better marketing and advertising purposes. In order to analyze user influence, we construct a user influence actor-network based on Actor-Network Theory, in which both users and users' microblogs are seen as actors and their interactions are treated as networks. User influence is then evolved into network effects caused by both microblogs and interactions, which are characterized as the Quality Index and Popularity Index of microblog respectively that can be well evaluated through models proposed in this paper. Furthermore, by observing that one user may show distinctive influence in different domains, we build our model domain specifically. With full consideration to quality, popularity and domain categories of users' microblogs, we propose a novel domain-specific user influence measurement, ANTRank, in Sin a Weibo based on Actor-Network Theory. Experimental results show that the ANTRank performs well with the user influence evaluation.