A Survey on Detecting Vandalism in Crowdsourcing Models

Crowdsourcing is a common term for collaborative environments that include a group of workers participating in the content of these platforms to create knowledge. The most important and well-known crowdsourcing platforms are Amazon's Mechanical Turk, Kaggle, Design99, and Wikipedia. Wikipedia is one of the most vital crowdsourcing models where users are contributing in creating and editing articles. Thus, leading to significant expansion in the encyclopedia that made it one of the most visited sites for getting information or using it as a knowledge base for many applications such as Chatbots. All These characteristics have come with another aspect through which users can sabotage the content of the encyclopedia that is known as vandalism. Vandalism is any attempt to modify the article in a way that negatively affects the article's quality. Vandalism is considered as one of the five layers model that constructed for cyber threads, which is known as cyber vandalism. Instead of misusing or stealing data, cyber vandalism involves all actions for damaging or destroying it. This paper presents a comprehensive survey that deals with various aspects of the vandalism detection problem in a crowdsourcing model - Wikipedia