Wikipedia Vandalism Detection: Combining Natural Language, Metadata, and Reputation Features
|Wikipedia Vandalism Detection: Combining Natural Language, Metadata, and Reputation Features|
|Author(s)||B. Adler, Luca de Alfaro, Santiago Mola-Velasco, Paolo Rosso, Andrew West|
|Published in||Lecture notes in computer science|
|Keyword(s)||Wikipedia, wiki, collaboration, vandalism, machine learning, metadata, natural-language processing, reputation (Extra: Vandalism detection, Vandal fighting, Spatio-temporal analysis)|
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Wikipedia Vandalism Detection: Combining Natural Language, Metadata, and Reputation Features is a 2011 publication written in English by B. Adler, Luca de Alfaro, Santiago Mola-Velasco, Paolo Rosso, Andrew West and published in Lecture notes in computer science.
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.
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