This paper explores a statistical language modeling approach for detecting Wikipedia vandalism. Wikipedia is a popular and influential collaborative information system. The collaborative nature of authoring, as well as the high visibility of its content, have exposed Wikipedia articles to vandalism, defined as malicious editing intended to compromise the integrity of the content of articles. Ex...

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 analysi...

The importance of collaborative social media (CSM) applications such as Wikipedia to modern free societies can hardly be overemphasized. By allowing end users to freely create and edit content, Wikipedia has greatly facilitated democratization of information. However, over the past several years, Wikipedia has also become susceptible to vandalism, which has adversely affected its information qu...

We present results of a new approach to detect destructive article revisions, so-called vandalism, in Wikipedia. Vandalism detection is a one-class classification problem, where vandalism edits are the target to be identified among all revisions. Interestingly, vandalism detection has not been addressed in the Information Retrieval literature by now. In this paper we discuss the characteristics...

Wikidata, like Wikipedia, is a knowledge base that anyone can edit. This open collaboration model is powerful in that it reduces barriers to participation and allows a large number of people to contribute. However, it exposes the knowledge base to the risk of vandalism and low-quality contributions. In this work, we build on past work detecting vandalism in Wikipedia to detect vandalism in Wiki...

Wikidata is the new, large-scale knowledge base of the Wikimedia Foundation. As it can be edited by anyone, entries frequently get vandalized, leading to the possibility that it might spread of falsified information if such posts are not detected. The WSDM 2017 Wiki Vandalism Detection Challenge requires us to solve this problem by computing a vandalism score denoting the likelihood that a revi...

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 syntacticsemantic m...

Graffiti and vandalism are everywhere in the modern city; they seem to be part of the typical urban background. While graffiti are usually associated with concrete walls, bridges and train cars, one particular area of focus of vandalistic writing is the walls and stalls of public bathrooms. This area, for both obvious, and sometimes unclear reasons, is a popular forum for anyone wanting to writ...