Expertise networks in online communities: structure and algorithms
Proceedings of the 16th international conference on World Wide Web
Identifying Opinion Leaders in BBS
WI-IAT '08 Proceedings of the 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Volume 03
Finding leaders from opinion networks
ISI'09 Proceedings of the 2009 IEEE international conference on Intelligence and security informatics
Detecting opinion leader dynamically in chinese news comments
WAIM'11 Proceedings of the 2011 international conference on Web-Age Information Management
An improved mix framework for opinion leader identification in online learning communities
Knowledge-Based Systems
Expert Systems with Applications: An International Journal
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Opinion leaders play a crucial role in online communities, which can guide the direction of public opinion. Most proposed algorithms on opinion leaders mining in internet social network are based on network structure and usually omit the fact that opinion leaders are field-limited and the opinion sentiment orientation analysis is the vital factor of one's authority. We propose a method to find the interest group based on topic content analysis, which combine the advantages of clustering and classification algorithms. Then we use the method of sentiment analysis to define the authority value as the weight of the link between users. On this basis, an algorithm named LeaderRank is proposed to identify the opinion leaders in BBS, and experiments indicate that Leader-Rank algorithm can effectively improve the accuracy of leaders mining.