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The illiterate editor: metadata-driven revert detection in Wikipedia
Conference proceeding

The illiterate editor: metadata-driven revert detection in Wikipedia

Jeffrey Segall and Rachel Greenstadt
Proceedings of the 9th International Symposium on open collaboration
05 Aug 2013

Abstract

As the community depends more heavily on Wikipedia as a source of reliable information, the ability to quickly detect and remove detrimental information becomes increasingly important. The longer incorrect or malicious information lingers in a source perceived as reputable, the more likely that information will be accepted as correct and the greater the loss to source reputation. We present The Illiterate Editor (IllEdit), a content-agnostic, metadata-driven classification approach to Wikipedia revert detection. Our primary contribution is in building a metadata-based feature set for detecting edit quality, which is then fed into a Support Vector Machine for edit classification. By analyzing edit histories, the IllEdit system builds a profile of user behavior, estimates expertise and spheres of knowledge, and determines whether or not a given edit is likely to be eventually reverted. The success of the system in revert detection (0.844 F-measure) as well as its disjoint feature set as compared to existing, content-analyzing vandalism detection systems, shows promise in the synergistic usage of IllEdit for increasing the reliability of community information.

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5 citations in Scopus

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