This paper addresses the challenge of efficiently mining meaningful knowledge from large and diverse online communities by developing schemes to discover and browse power users based on their activities. It introduces new features to describe user activities and interactions, emphasizing the effectiveness of the cross reference (CR) feature in identifying power users. Additionally, a novel interface is proposed for exploring power users, with two schemes for navigating a large number of candidates. Experimental results demonstrate the effectiveness of the CR rank in discovering power users with high precision and minimal false alarms.
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Shin, Hyoseop, Zhiwei Xu, and Eun-Yi Kim. "Discovering and browsing of power users by social relationship analysis in large-scale online communities." 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology. Vol. 1. IEEE, 2008.
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