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A content-driven reputation system for the Wikipedia
Abstract We present a content-driven reputation sWe 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.
Abstractsub We present a content-driven reputation sWe 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.
Bibtextype misc  +
Citeulike 1291537  +
Doi 10.1145/1242572.1242608  +
Has author B. Thomas Adler + , Luca de Alfaro +
Has remote mirror http://www.soe.ucsc.edu/~luca/papers/06/ucsc-crl-06-18.pdf  +
Language English +
Number of citations by publication 10  +
Number of references by publication 0  +
Pages 261-270  +
Related tool WikiTrust +
Title A content-driven reputation system for the Wikipedia +
Type unknown  +
Year 2007 +
Creation dateThis property is a special property in this wiki. 28 January 2012 21:09:46  +
Categories Publications without published in parameter  + , Publications without keywords parameter  + , Publications without license parameter  + , Publications without archive mirror parameter  + , Publications without paywall mirror parameter  + , Publications without references parameter  + , Publications  +
Modification dateThis property is a special property in this wiki. 6 November 2012 13:17:55  +
DateThis property is a special property in this wiki. 2007  +
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A content-driven reputation system for the Wikipedia + Title
 

 

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