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

Identifying Topic-Specific Experts on Microblog

Vol. 10, No. 6, June 29, 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.


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Cite this article

[IEEE Style]
Y. Yu, L. Mo, J. 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]
Yan Yu, Lingfei Mo, and Jian Wang. 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.

[BibTeX Style]
@article{tiis:21129, title="Identifying Topic-Specific Experts on Microblog", author="Yan Yu and Lingfei Mo and Jian Wang and ", journal="KSII Transactions on Internet and Information Systems", DOI={10.3837/tiis.2016.06.010}, volume={10}, number={6}, year="2016", month={June}, pages={2627-2647}}