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Proceedings Article: BibTeX citation key:  adler.648
Adler Thomas B. & de Alfaro Luca (2007). « A Content-Driven Reputation System for the Wikipedia ». In 16th International World Wide Web Conference, 8-12 mai 2007.
Added by: Laure Endrizzi 2007-11-16 05:08:11    Last edited by: Laure Endrizzi 2007-11-24 09:07:51
Categories: 4. interfaces et modes de consultation
Keywords: ergonomie, extraction d'information, régulation, travail collaboratif, Wikipedia
Creators: Adler, de Alfaro
Collection: 16th International World Wide Web Conference

Number of views:  1313
Popularity index:  10.99%

 
Abstract
On-line forums for the collaborative creation of bodies of information are a phenomenon of rising importance; the Wikipedia is one of the best-known examples. The open nature of such forums could benefit from a notion of reputation for its authors. Author reputation could be used to flag new contributions from low-reputation authors, and it could be used to allow only authors with good reputation to contribute to controversial or critical pages. A reputation system for the Wikipedia would also provide an incentive to give high-quality contributions.

We present in this paper a novel type of content-driven reputation system for Wikipedia authors. In our system, authors gain reputation when the edits and text additions they perform to Wikipedia articles are long-lived, and they lose reputation when their changes are undone in short order. 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, and of being undone.
Added by: Laure Endrizzi    Last edited by: Laure Endrizzi

 
Further information may be found at:
http://www2007.org/paper692.php

 
Notes

Added by: Laure Endrizzi    Last edited by: Laure Endrizzi

 
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