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Wikipedia is an online encyclopedia that anyone can edit. In this open model,some people edits with the intent of harming the integrity of Wikipedia. Thisis known as vandalism. We extend the framework presented in (Potthast, Stein,and Gerling, 2008) for Wikipedia vandalism detection. In this approach, severalvandalism indicating features are extracted from edits in a vandalism corpusand are fed to a supervised learning algorithm. The best performing classifierswere LogitBoost and Random Forest. Our classifier, a Random Forest, obtained anAUC of 0.92236, ranking in the first place of the PAN'10 Wikipedia vandalismdetection task.

Wikipedia Vandalism Detection Through Machine Learning: Feature Review and New Proposals: Lab Report for PAN at CLEF 2010