• KSII Transactions on Internet and Information Systems
    Monthly Online Journal (eISSN: 1976-7277)

Identifying Topic-Specific Experts on Microblog

Vol. 10, No.6, June 30, 2016
10.3837/tiis.2016.06.010, Download Paper (Free):

Abstract

With the rapid growth of microblog, expert identification on microblog has been playing a crucial role in many applications. While most previous expert identification studies only assess global authoritativeness of a user, there is no way to differentiate the authoritativeness in a particular aspect of topics. In this paper, we propose a novel model, which jointly models text and following relationship in the same generative process. Furthermore, we integrate a similarity-based weight scheme into the model to address the popular bias problem, and use followee topic distribution as prior information to make user's topic distribution more precisely. Our empirical study on two large real-world datasets shows that our proposed model produces significantly higher quality results than the prior arts.


Statistics

Show / Hide Statistics

Statistics (Cumulative Counts from December 1st, 2015)
Multiple requests among the same browser session are counted as one view.
If you mouse over a chart, the values of data points will be shown.


Cite this article

[IEEE Style]
Yan Yu, Lingfei Mo and Jian Wang, "Identifying Topic-Specific Experts on Microblog," KSII Transactions on Internet and Information Systems, vol. 10, no. 6, pp. 2627-2647, 2016. DOI: 10.3837/tiis.2016.06.010

[ACM Style]
Yu, Y., Mo, L., and Wang, J. 2016. Identifying Topic-Specific Experts on Microblog. KSII Transactions on Internet and Information Systems, 10, 6, (2016), 2627-2647. DOI: 10.3837/tiis.2016.06.010