The anatomy of a large-scale hypertextual Web search engine
WWW7 Proceedings of the seventh international conference on World Wide Web 7
TwitterRank: finding topic-sensitive influential twitterers
Proceedings of the third ACM international conference on Web search and data mining
Finding influentials based on the temporal order of information adoption in twitter
Proceedings of the 19th international conference on World wide web
Identifying topical authorities in microblogs
Proceedings of the fourth ACM international conference on Web search and data mining
Everyone's an influencer: quantifying influence on twitter
Proceedings of the fourth ACM international conference on Web search and data mining
Influence and passivity in social media
ECML PKDD'11 Proceedings of the 2011 European conference on Machine learning and knowledge discovery in databases - Volume Part III
Cognos: crowdsourcing search for topic experts in microblogs
SIGIR '12 Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval
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With a huge number of active users on microblogs, it becomes increasingly important to identify authoritative users on specific topics. This paper tackles the task of finding authorities on Twitter given any query topic. Although there exists much work on identifying influential users on Twitter, most of them focus on global authority regardless of the topic. We propose a novel Topical Authority Propagation (TAP) model by utilizing the fact that topical authority can be propagated through retweeting, i.e., if a user's tweet on a given topic is retweeted by a topical authority, that user is likely to be an authority on the topic as well. Topical relevance of candidate authorities can be seamlessly integrated into the model. Link analysis algorithms such as PageRank can then be utilized to characterize how topical authority is propagated through retweeting. We conduct a set of experiments on Twitter and demonstrate the effectiveness of the proposed approach.