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Twitterrank: finding topic-sensitive influential twitterers (2010)
| Venue: | IN IN PROCEEDINGS OF THE 3RD INTERNATIONAL CONFERENCE ON WEB SEARCH AND DATA MINING |
| Citations: | 285 - 12 self |
BibTeX
@INPROCEEDINGS{Weng10twitterrank:finding,
author = {Jianshu Weng and Ee-peng Lim and Jing Jiang and Qi He},
title = {Twitterrank: finding topic-sensitive influential twitterers},
booktitle = {IN IN PROCEEDINGS OF THE 3RD INTERNATIONAL CONFERENCE ON WEB SEARCH AND DATA MINING},
year = {2010},
publisher = {}
}
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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 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
