Adler, B.T., de Alfaro, L., Mola-Velasco, S.M., Rosso, P., and West, A.G. 
(2011). Wikipedia Vandalism Detection: Combining Natural Language,
Metadata, and Reputation Features. In CICLing '11: Proceedings of the 12th
International Conference on Intelligent Text Processing and Computational
Linguistics, LNCS 6609, pp. 277-288. Tokyo, Japan.


Abstract: Wikipedia is an online encyclopedia which anyone can edit. While
most edits are constructive, about 7% are acts of vandalism. Such behavior
is characterized by modifications made in bad faith; introducing spam and
other inappropriate content.

In this work, we present the results of an effort to integrate three of the
leading approaches to Wikipedia vandalism detection: a spatio-temporal
analysis of metadata (STiki), a reputation-based system (WikiTrust), and
natural language processing features.  The performance of the resulting
joint system improves the state-of-the-art from all previous methods and
establishes a new baseline for Wikipedia vandalism detection. We examine in
detail the contribution of the three approaches, both for the task of
discovering fresh vandalism, and for the task of locating vandalism in the
complete set of Wikipedia revisions.