Sciweavers

Share
WSDM
2010
ACM

TwitterRank: Finding Topic-sensitive Influential Twitterers

10 years 12 months ago
TwitterRank: Finding Topic-sensitive Influential Twitterers
This paper focuses on the problem of identifying influential users of micro-blogging services. Twitter, one of the most notable micro-blogging services, employs a social-networking model called "following", in which each user can choose who she wants to "follow" to receive tweets from without requiring the latter to give permission first. In a dataset prepared for this study, it is observed that (1) 72.4% of the users in Twitter follow more than 80% of their followers, and (2) 80.5% of the users have 80% of users they are following follow them back. Our study reveals that the presence of "reciprocity" can be explained by phenomenon of homophily [14]. Based on this finding, TwitterRank, an extension of PageRank algorithm, is proposed to measure the influence of users in Twitter. TwitterRank measures the influence taking both the topical similarity between users and the link structure into account. Experimental results show that TwitterRank outperforms the ...
Jianshu Weng, Ee-peng Lim, Jing Jiang, Qi He
Added 01 Mar 2010
Updated 02 Mar 2010
Type Conference
Year 2010
Where WSDM
Authors Jianshu Weng, Ee-peng Lim, Jing Jiang, Qi He
Comments (0)
books