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A content-context-centric approach for detecting vandalism in Wikipedia | IEEE Conference Publication | IEEE Xplore

A content-context-centric approach for detecting vandalism in Wikipedia


Abstract:

Collaborative online social media (CSM) applications such as Wikipedia have not only revolutionized the World Wide Web, but they also have had a hugely positive effect on...Show More

Abstract:

Collaborative online social media (CSM) applications such as Wikipedia have not only revolutionized the World Wide Web, but they also have had a hugely positive effect on modern free societies. Unfortunately, Wikipedia has also become target to a wide-variety of vandalism attacks. Most existing vandalism detection techniques rely upon simple textual features such as existence of abusive language or spammy words. These techniques are ineffective against sophisticated vandal edits, which often do not contain the tell-tale markers associated with vandalism. In this paper, we argue for a context-aware approach for vandalism detection. This paper proposes a content-context-aware vandalism detection framework. The main idea is to quantify how well the words contained in the edit fit into the topic and the existing content of the Wikipedia article. We present two novel metrics, called WWW co-occurrence probability and top-ranked co-occurrence probability for this purpose. We also develop efficient mechanisms for evaluating these two metrics, and machine learning-based schemes that utilize these metrics. The paper presents a range of experiments to demonstrate the effectiveness of the proposed approach.
Date of Conference: 20-23 October 2013
Date Added to IEEE Xplore: 12 December 2013
Electronic ISBN:978-1-936968-92-3
Conference Location: Austin, TX, USA

References

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