A content-driven reputation system for the Wikipedia

From WikiLit
Jump to: navigation, search
Publication (help)
A content-driven reputation system for the Wikipedia
Authors: B. Thomas Adler, Luca de Alfaro [edit item]
Citation: WWW '07 Proceedings of the 16th international conference on World Wide Web  : 261-270. 2007.
Publication type: Conference paper
Peer-reviewed: Yes
Database(s):
DOI: Define doi.
Google Scholar cites: Citations
Link(s): Paper link
Added by Wikilit team: Added on initial load
Search
Article: Google Scholar BASE PubMed
Other scholarly wikis: AcaWiki Brede Wiki WikiPapers
Web search: Bing Google Yahoo!Google PDF
Other:
Services
Format: BibTeX
A content-driven reputation system for the Wikipedia is a publication by B. Thomas Adler, Luca de Alfaro.


[edit] Abstract

We 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.

[edit] Research questions

"We 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."

Research details

Topics: Reputation systems [edit item]
Domains: Computer science [edit item]
Theory type: Design and action [edit item]
Wikipedia coverage: Main topic [edit item]
Theories: "Information theory" [edit item]
Research design: Mathematical modeling [edit item]
Data source: Wikipedia pages [edit item]
Collected data time dimension: Longitudinal [edit item]
Unit of analysis: Edit, User [edit item]
Wikipedia data extraction: Dump [edit item]
Wikipedia page type: Article, History [edit item]
Wikipedia language: French, Italian [edit item]

[edit] Conclusion

"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."

[edit] Comments

"The content-driven user reputation algorithm proposed has been able to predict on average users' reputation based on the quality of their contribution."


Further notes[edit]