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Automatic vandalism detection in Wikipedia
Abstract We present results of a new approach to deWe present results of a new approach to detect destructive article revisions, so-called vandalism, inWikipedia. Vandalism detection is a one-class classification problem, where vandalism edits are the target to be identified among all revisions. Interestingly, vandalism detection has not been addressed in the Information Retrieval literature by now. In this paper we discuss the characteristics of vandalism as humans recognize it and develop features to render vandalism detection as a machine learning task. We compiled a large number of vandalism edits in a corpus, which allows for the comparison of existing and new detection approaches. Using logistic regression we achieve 83% precision at 77% recall with our model. Compared to the rule-based methods that are currently applied in Wikipedia, our approach increases the F-Measure performance by 49% while being faster at the same time.y 49% while being faster at the same time.
Added by wikilit team Added on initial load  +
Collected data time dimension Longitudinal  +
Conclusion Potthast et al. **** presented a new approPotthast et al. **** presented a new approach to detect Vandalism in Wikipedia based on Logistic Regression, a machine learning classification. algorithm. The classification task is accomplished based on various features extracted to quantify the characteristics of Vandalism in Wikipedia articles. These features include term frequency, character distribution, edit anonymity. This approach achieved 83% precision at 77% recall.oach achieved 83% precision at 77% recall.
Conference location Berlin, Heidelberg +
Data source Wikipedia pages  +
Google scholar url http://scholar.google.com/scholar?ie=UTF-8&q=%22Automatic%2Bvandalism%2Bdetection%2Bin%2BWikipedia%22  +
Has author Martin Potthast + , Benno Stein + , Robert Gerling +
Has domain Computer science +
Has topic Vandalism +
Pages 663-668  +
Peer reviewed Yes  +
Publication type Conference paper  +
Published in European Conference on Information Retrieval +
Publisher Springer-Verlag +
Research design Statistical analysis  +
Research questions In this paper we discuss the characteristiIn this paper we discuss the characteristics of vandalism as humans recognize it and develop features to render vandalism detection as a machine learning task. We compiled a large number of vandalism edits in a corpus, which allows for the comparison of existing and new detection approaches. of existing and new detection approaches.
Revid 10,671  +
Theories Undetermined
Theory type Design and action  +
Title Automatic vandalism detection in Wikipedia
Unit of analysis Article  +
Url http://www.springerlink.com/content/a457383n01w44653/  +
Wikipedia coverage Main topic  +
Wikipedia data extraction Secondary dataset  +
Wikipedia language English  +
Wikipedia page type Article  +
Year 2008  +
Creation dateThis property is a special property in this wiki. 15 March 2012 20:24:08  +
Categories Vandalism  + , Computer science  + , Publications with missing comments  + , Publications  +
Modification dateThis property is a special property in this wiki. 30 January 2014 20:20:46  +
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