Abstract
Vandalism of the content has always been one of the greatest problems for Wikipedia, yet only few completely automatic solutions for solving it have been developed so far. Volunteers still spend large amounts of time correcting vandalized page edits, instead of using this time to improve the quality of the content of articles. The purpose of this paper is to introduce a new vandalism detection system, that only uses natural language processing and machine learning techniques. The system has been evaluated on a corpus of real vandalized data in order to test its performance and justify the design choices. The same expert annotated wikitext, extracted from the encyclopedia’s database, is used to evaluate different vandalism detection algorithms. The paper presents a critical analysis of the obtained results, comparing them to existing solutions, and suggests different statistical classification methods that bring several improvements to the task at hand.
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Cioiu, D., Rebedea, T. (2013). WikiDetect: Automatic Vandalism Detection for Wikipedia Using Linguistic Features. In: Bǎdicǎ, C., Nguyen, N.T., Brezovan, M. (eds) Computational Collective Intelligence. Technologies and Applications. ICCCI 2013. Lecture Notes in Computer Science(), vol 8083. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40495-5_32
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DOI: https://doi.org/10.1007/978-3-642-40495-5_32
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