Harnessing Context for Vandalism Detection in Wikipedia

Journal Title: EAI Endorsed Transactions on Collaborative Computing - Year 2015, Vol 1, Issue 1

Abstract

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 quality. Traditional vandalism detection techniques that rely upon simple textual features such as spammy or abusive words have not been very effective in combating sophisticated vandal attacks that do not contain common vandalism markers. In this paper, we propose a context-based vandalism detection framework for Wikipedia. We first propose a contextenhanced finite state model for representing the context evolution ofWikipedia articles. This paper identifies two distinct types of context that are potentially valuable for vandalism detection, namely content-context and contributor-context. The distinguishing powers of these contexts are discussed by providing empirical results. We design two novel metrics for measuring how well the content-context of an incoming edit fits into the topic and the existing content of a Wikipedia article. We outline machine learning-based vandalism identification schemes that utilize these metrics. Our experiments indicate that utilizing context can substantially improve vandalism detection accuracy.

Authors and Affiliations

Lakshmish Ramaswamy, Raga Sowmya Tummalapenta, Deepika Sethi, Kang Li, Calton Pu

Keywords

Related Articles

Achieving Security Assurance with Assertion-based Application Construction

Modern software applications are commonly built by leveraging pre-fabricated modules, e.g. application programming interfaces (APIs), which are essential to implement the desired functionalities of software applications,...

Harnessing Context for Vandalism Detection in Wikipedia

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 faci...

Lighting controls and energy savings potential in tropical zone

Reducing global energy consumption is a challenge to limit the rise in average earth temperature. The use of lighting controls in the building leads to energy savings. The objective of this study is to evaluate the energ...

Testing Software Using Swarm Intelligence: A Bee Colony Optimization Approach

Software testing is a critical activity in increasing our confidence of a system under test and improving its quality. The key idea for testing a software application is to minimize the number of faults found in the syst...

Effects of Cohesion-Based Feedback on the Collaborations in Global Software Development Teams

This paper describes a study that examines the effect of cohesion-based feedback on a team member’s behaviors in a global software development project. Chat messages and forum posts were collected from a software develop...

Download PDF file
  • EP ID EP45680
  • DOI http://dx.doi.org/10.4108/cc.1.1.e7
  • Views 447
  • Downloads 0

How To Cite

Lakshmish Ramaswamy, Raga Sowmya Tummalapenta, Deepika Sethi, Kang Li, Calton Pu (2015). Harnessing Context for Vandalism Detection in Wikipedia. EAI Endorsed Transactions on Collaborative Computing, 1(1), -. https://europub.co.uk/articles/-A-45680