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Modeling user reputation in wikis
Abstract Collaborative systems available on the WebCollaborative systems available on the Web allow millions of users to share information through a growing collection of tools and platforms such as wikis, blogs, and shared forums. By their very nature, these systems contain resources and information with different quality levels. The open nature of these systems, however, makes it difficult for users to determine the quality of the available information and the reputation of its providers. Here, we first parse and mine the entire English Wikipedia history pages in order to extract detailed user edit patterns and statistics. We then use these patterns and statistics to derive three computational models of a user's reputation. Finally, we validate these models using ground-truth Wikipedia data associated with vandals and administrators. When used as a classifier, the best model produces an area under the receiver operating characteristic {(ROC)} curve {(AUC)} of 0.98. Furthermore, we assess the reputation predictions generated by the models on other users, and show that all three models can be used efficiently for predicting user behavior in Wikipedia.for predicting user behavior in Wikipedia.
Abstractsub Collaborative systems available on the WebCollaborative systems available on the Web allow millions of users to share information through a growing collection of tools and platforms such as wikis, blogs, and shared forums. By their very nature, these systems contain resources and information with different quality levels. The open nature of these systems, however, makes it difficult for users to determine the quality of the available information and the reputation of its providers. Here, we first parse and mine the entire English Wikipedia history pages in order to extract detailed user edit patterns and statistics. We then use these patterns and statistics to derive three computational models of a user's reputation. Finally, we validate these models using ground-truth Wikipedia data associated with vandals and administrators. When used as a classifier, the best model produces an area under the receiver operating characteristic {(ROC)} curve {(AUC)} of 0.98. Furthermore, we assess the reputation predictions generated by the models on other users, and show that all three models can be used efficiently for predicting user behavior in Wikipedia.for predicting user behavior in Wikipedia.
Bibtextype article  +
Doi 10.1002/sam.v3:2  +
Has author Sara Javanmardi + , Cristina Lopes + , Pierre Baldi +
Has keyword Web 2.0 + , Wiki + , Wiki mining + , Wikipedia + , Reliability + , Reputation +
Issn 1932-1864  +
Issue 2  +
Language English +
Number of citations by publication 2  +
Number of references by publication 0  +
Pages 126-139  +
Published in Statistical Analysis and Data Mining +
Title Modeling user reputation in wikis +
Type journal article  +
Volume 3  +
Year 2010 +
Creation dateThis property is a special property in this wiki. 29 April 2012 12:16:33  +
Categories Publications without license parameter  + , Publications without remote mirror parameter  + , Publications without archive mirror parameter  + , Publications without paywall mirror parameter  + , Journal articles  + , Publications without references parameter  + , Publications  +
Modification dateThis property is a special property in this wiki. 20 September 2014 18:13:24  +
DateThis property is a special property in this wiki. 2010  +
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Circadian patterns of Wikipedia editorial activity: A demographic analysis + , Dynamics of Conflicts in Wikipedia + Has reference
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