This study focuses on understanding the long-tailed distributions of user behavior in content creation and rating on community websites, using Essembly as a case study. It goes beyond merely describing these patterns by proposing mechanisms that are rooted in individual user behaviors, considering the information available to each user. The research identifies significant variations in user activity rates, the amount of time spent on the site, and the qualities of the content being rated as the primary factors behind the observed long-tailed distributions. Furthermore, the proposed models offer insights into predicting the properties of users and content based on early behaviors, providing a deeper understanding of dynamics within online community sites.
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Hogg, Tad, and Gabor Szabo. "Diversity of user activity and content quality in online communities." Proceedings of the International AAAI Conference on Web and Social Media. Vol. 3. No. 1. 2009.
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