SODA '03 Proceedings of the fourteenth annual ACM-SIAM symposium on Discrete algorithms
Agreeing to disagree: search engines and their public interfaces
Proceedings of the 7th ACM/IEEE-CS joint conference on Digital libraries
Characterizing user behavior in online social networks
Proceedings of the 9th ACM SIGCOMM conference on Internet measurement conference
TwitterRank: finding topic-sensitive influential twitterers
Proceedings of the third ACM international conference on Web search and data mining
What is Twitter, a social network or a news media?
Proceedings of the 19th international conference on World wide web
WISE'12 Proceedings of the 13th international conference on Web Information Systems Engineering
Microblog searching module based on community detection
ICIC'13 Proceedings of the 9th international conference on Intelligent Computing Theories
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Sina Micro-blog is the first micro-blogging service in China and is growing fast in recent two years. This paper first studies the characteristics of Sina online social network and then focuses on the problem of indentifying influential users. In a dataset prepared for this study, we find an approximate power-law follower distribution and a non-power-law friend distribution, a log correlation between follower number and tweet number, some time-distributing and geographical characteristics. We also find that the growing trend of Mobile market in China strongly affects the growing of micro-blogging service. In order to find the most popular users, we propose our algorithm called XinRank and compared it with the other two algorithms. The result shows that XinRank is different and really offers a new perspective for people to find these users. Also, our algorithm is dynamic and stability, which is special and better than the other two algorithms.