vandalism

Language of Vandalism: Improving Wikipedia Vandalism Detection via Stylometric Analysis

Community-based knowledge forums, such as Wikipedia, are susceptible to vandalism, i.e., ill-intentioned contributions that are detrimental to the quality of collective intelligence. Most previous work to date relies on shallow lexico-syntactic patterns and metadata to automatically detect vandalism in Wikipedia. In this paper, we explore more linguistically motivated approaches to vandalism de...

Detecting Wikipedia Vandalism

Since its inception in 2001, Wikipedia has become the largest encyclopedia ever created in human history. With over 4 million articles in the English edition alone, it has become the highest-traffic educational website on the Internet. It receives over 100,000 edits per day, which can be daunting for human editors to monitor for vandalism, spam, or other inappropriate content. While there are e...

Automatic Vandalism Detection in Wikipedia

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...

Beyond vandalism: Wikipedia trolls

Research on trolls is scarce, but their activities challenge online communities; one of the main challenges of the Wikipedia community is to fight against vandalism and trolls. This study identifies Wikipedia trolls' behaviours and motivations, and compares and contrasts hackers with trolls; it extends our knowledge about this type of vandalism and concludes that Wikipedia trolls are one type o...

Wiki Vandalysis - Wikipedia Vandalism Analysis

Wikipedia describes itself as the “free encyclopedia that anyone can edit”. Along with the helpful volunteers who contribute by improving the articles, a great number of malicious users abuse the open nature of Wikipedia by vandalizing articles. Deterring and reverting vandalism has become one of the major challenges of Wikipedia as its size grows. Wikipedia editors fight vandalism both manuall...

Detecting Vandalism in Wikipedia Edits

Ensemble Models for Detecting Wikidata Vandalism with Stacking - Team Honeyberry Vandalism Detector at WSDM Cup 2017

The WSDM Cup 2017 is a binary classification task for classifying Wikidata revisions into vandalism and non-vandalism. This paper describes our method using some machine learning techniques such as under-sampling, feature selection, stacking and ensembles of models. We confirm the validity of each technique by calculating AUC-ROC of models using such techniques and not using them. Additionally,...