2011 UserReputationinaCommentRatingE

• (Chen et al., 2011) ⇒ Bee-Chung Chen, Jian Guo, Belle Tseng, and Jie Yang. (2011). “User Reputation in a Comment Rating Environment.” In: Proceedings of the 17th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD-2011) Journal. ISBN:978-1-4503-0813-7 doi:10.1145/2020408.2020439

Subject Headings:

Cited By

• http://scholar.google.com/scholar?q=%222011%22+User+Reputation+in+a+Comment+Rating+Environment
• http://dl.acm.org/citation.cfm?id=2020408.2020439&preflayout=flat#citedby

Quotes

Author Keywords

• Algorithms; bias removal; experimentation; hierarchical smoothing; human factors; latent factor model; measurement; tensor factorization; text quality; user profiles and alert services

Abstract

Reputable users are valuable assets of a web site. We focus on user reputation in a comment rating environment, where users make comments about content items and rate the comments of one another. Intuitively, a reputable user posts high quality comments and is highly rated by the user community. To our surprise, we find that the quality of a comment judged editorially is almost uncorrelated with the ratings that it receives, but can be predicted using standard text features, achieving accuracy as high as the agreement between two editors ! However, extracting a pure reputation signal from ratings is difficult because of data sparseness and several confounding factors in users' voting behavior. To address these issues, we propose a novel bias-smoothed tensor model and empirically show that our model significantly outperforms a number of alternatives based on Yahoo ! News, Yahoo ! Buzz and Epinions datasets.

References

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	Author	volume	Date Value	title	type	journal	titleUrl	doi	note	year
2011 UserReputationinaCommentRatingE	Bee-Chung Chen Belle Tseng Jian Guo Jie Yang			User Reputation in a Comment Rating Environment				10.1145/2020408.2020439		2011