Presentations (Communicative Events)

“Got You!”: Automatic Vandalism Detection in Wikipedia
with Web-based Shallow Syntactic-Semantic Modeling

McKeown, Kathleen; Wang, William

Discriminating vandalism edits from non-vandalism edits in Wikipedia is a challenging task, as ill-intentioned edits can include a variety of content and be expressed in many different forms and styles. Previous studies are limited to rule-based methods and learning based on lexical features, lacking in linguistic analysis. In this paper, we propose a novel Web-based shallow syntactic-semantic modeling method, which utilizes Web search results as resource and trains topic-specific n-tag and syntactic n-gram language models to detect vandalism. By combining basic task-specific and lexical features, we have achieved
high F-measures using logistic boosting and logistic model trees classifiers, surpassing the results reported by major Wikipedia vandalism detection systems.



More About This Work

Academic Units
Computer Science
Published Here
April 29, 2013