Authoritative sources in a hyperlinked environment
Journal of the ACM (JACM)
Objectrank: authority-based keyword search in databases
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
TwitterRank: finding topic-sensitive influential twitterers
Proceedings of the third ACM international conference on Web search and data mining
Identifying topical authorities in microblogs
Proceedings of the fourth ACM international conference on Web search and data mining
Topical semantics of twitter links
Proceedings of the fourth ACM international conference on Web search and data mining
Influence and passivity in social media
Proceedings of the 20th international conference companion on World wide web
TI: an efficient indexing mechanism for real-time search on tweets
Proceedings of the 2011 ACM SIGMOD International Conference on Management of data
TURank: twitter user ranking based on user-tweet graph analysis
WISE'10 Proceedings of the 11th international conference on Web information systems engineering
LBSNRank: personalized pagerank on location-based social networks
Proceedings of the 2012 ACM Conference on Ubiquitous Computing
An in-browser microblog ranking engine
ER'12 Proceedings of the 2012 international conference on Advances in Conceptual Modeling
Finding news curators in twitter
Proceedings of the 22nd international conference on World Wide Web companion
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Most users play two roles in micro-blog, namely, author and reader of tweets. Facing diverse users and mass user-generated contents in micro-blog, identifying and ranking influential authors who post topic-specific high-quality contents is a challenge. In this paper, we present a way to measure the quality of tweets, which accordingly determines the influence of their authors. The quality of the tweet is evaluated according to the topic focus degree, the retweeting behavior, and the topic-specific influence of the users who retweet it. In this way, the relationships between two micro-blog users extend beyond the traditional following (i.e., friend -follower ) relationship to have more that are established indirectly and dynamically through tweets. We explore the use of these enriched relationships and present a tweet-centric topic-specific author ranking in micro-blog. To enable timely mass data processing on a daily or even hourly basis, we implement our ranking method using MapReduce framework. Some evaluation experiments have been conducted based on a large-scaled real dataset from Tencent micro-blog, which has the largest number of users (over 200 millions) in China. The result shows that our author ranking approach outperforms the PageRank-based and HITS-based approaches significantly in terms of ranking accuracy and quality.