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Detecting Wikipedia vandalism with a contributing efficiency-based approach
Abstract The collaborative nature of wiki has distiThe collaborative nature of wiki has distinguished Wikipedia as an online encyclopedia but also makes the open contents vulnerable against vandalism. The current vandalism detection methods relying on basic statistic language features work well for explicitly offensive edits that perform massive changes. However, these techniques are evadable for the elusive vandal edits which make only a few unproductive or dishonest modifications. In this paper we proposed a contributing efficiency-based approach to detect the vandalism in Wikipedia and implement it with machine-learning based classifiers that incorporate the contributing efficiency along with other languages features. The results of extensional experiment show that the contributing efficiency can improve the recall of machine learning-based vandalism detection algorithms significantly.dalism detection algorithms significantly.
Abstractsub The collaborative nature of wiki has distiThe collaborative nature of wiki has distinguished Wikipedia as an online encyclopedia but also makes the open contents vulnerable against vandalism. The current vandalism detection methods relying on basic statistic language features work well for explicitly offensive edits that perform massive changes. However, these techniques are evadable for the elusive vandal edits which make only a few unproductive or dishonest modifications. In this paper we proposed a contributing efficiency-based approach to detect the vandalism in Wikipedia and implement it with machine-learning based classifiers that incorporate the contributing efficiency along with other languages features. The results of extensional experiment show that the contributing efficiency can improve the recall of machine learning-based vandalism detection algorithms significantly.dalism detection algorithms significantly.
Bibtextype inproceedings  +
Doi 10.1007/978-3-642-35063-4_48  +
Has author Tang X. + , Guangyou Zhou + , Fu Y. + , Gan L. + , Yu W. + , Li S. +
Has extra keyword Detection algorithm + , Detection methods + , Language features + , Machine learning + , Online encyclopedia + , Open content + , Wikipedia + , Classification (of information) + , Learning systems + , Systems engineering + , Websites + , Efficiency +
Has keyword Classification + , Vandalism detection + , Wikipedia +
Isbn 9783642350627  +
Language English +
Number of citations by publication 0  +
Number of references by publication 0  +
Pages 645–651  +
Published in Lecture Notes in Computer Science +
Title Detecting Wikipedia vandalism with a contributing efficiency-based approach +
Type conference paper  +
Volume 7651 LNCS  +
Year 2012 +
Creation dateThis property is a special property in this wiki. 7 November 2014 15:30:41  +
Categories Publications without license parameter  + , Publications without remote mirror parameter  + , Publications without archive mirror parameter  + , Publications without paywall mirror parameter  + , Conference papers  + , Publications without references parameter  + , Publications  +
Modification dateThis property is a special property in this wiki. 7 November 2014 15:30:41  +
DateThis property is a special property in this wiki. 2012  +
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