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A content-driven reputation system for the Wikipedia
Abstract We present a content-driven reputation sysWe present a content-driven reputation system for Wikipedia authors. In our system, authors gain reputation when the edits they perform to Wikipedia articles are preserved by subsequent authors, and they lose reputation when their edits are rolled back or undone in short order. Thus, author reputation is computed solely on the basis of content evolution; user-to-user comments or ratings are not used. The author reputation we compute could be used to flag new contributions from low-reputation authors, or it could be used to allow only authors with high reputation to contribute to controversialor critical pages. A reputation system for the Wikipedia could also provide an incentive for high-quality contributions. We have implemented the proposed system, and we have used it to analyze the entire Italian and French Wikipedias, consisting of a total of 691, 551 pages and 5, 587, 523 revisions. Our results show that our notion of reputation has good predictive value: changes performed by low-reputation authors have a significantly larger than average probability of having poor quality, as judged by human observers, and of being later undone, as measured by our algorithms.ter undone, as measured by our algorithms.
Added by wikilit team Added on initial load  +
Collected data time dimension Longitudinal  +
Comments The content-driven user reputation algorithm proposed has been able to predict on average users' reputation based on the quality of their contribution.
Conclusion Our results show that our notion of reputaOur results show that our notion of reputation has good predictive value: changes performed by low-reputation authors have a significantly larger than average probability of having poor quality, as judged by human observers, and of being later undone, as measured by our algorithms.ter undone, as measured by our algorithms.
Data source Wikipedia pages  +
Google scholar url http://scholar.google.com/scholar?ie=UTF-8&q=%22A%2Bcontent-driven%2Breputation%2Bsystem%2Bfor%2Bthe%2BWikipedia%22  +
Has author B. Thomas Adler + , Luca de Alfaro +
Has domain Computer science +
Has topic Reputation systems +
Pages 261-270  +
Peer reviewed Yes  +
Publication type Conference paper  +
Published in WWW '07 Proceedings of the 16th international conference on World Wide Web +
Research design Mathematical modeling  +
Research questions We present a content-driven reputation sysWe present a content-driven reputation system for Wikipedia authors. In our system, authors gain reputa- tion when the edits they perform to Wikipedia articles are preserved by subsequent authors, and they lose reputation when their edits are rolled back or undone in short order. Thus, author reputation is computed solely on the basis of content evolution; user-to-user comments or ratings are not used. The author reputation we compute could be used to flag new contributions from low-reputation authors, or it could be used to allow only authors with high reputation to contribute to controversial or critical pages. A reputation system for the Wikipedia could also provide an incentive for high-quality contributions. We have implemented the proposed system, and we have used it to analyze the entire Italian and French Wikipedias, consisting of a total of 691,551 pages and 5,587,523 revi- sions.f 691,551 pages and 5,587,523 revi- sions.
Revid 10,630  +
Theories Information theory
Theory type Design and action  +
Title A content-driven reputation system for the Wikipedia
Unit of analysis Edit  + , User  +
Url http://works.bepress.com/luca_de_alfaro/3/  +
Wikipedia coverage Main topic  +
Wikipedia data extraction Dump  +
Wikipedia language French  + , Italian  +
Wikipedia page type Article  + , History  +
Year 2007  +
Creation dateThis property is a special property in this wiki. 13 March 2012 12:20:12  +
Categories Reputation systems  + , Computer science  + , Publications  +
Modification dateThis property is a special property in this wiki. 30 January 2014 20:19:31  +
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