TwitterRank: Finding topic-sensitive influential Twitterers

Abstract

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 requir-ing 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