# Online Disinformation and the Role of Wikipedia

arXiv: https://arxiv.org/abs/1910.12596 · HTML: https://mlsanity.com/paper/1910.12596/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 14 Oct 2019.

## Built on by (most cited first, 4 of 4)

- [WikiContradiction: Detecting Self-Contradiction Articles on Wikipedia](https://mlsanity.com/paper/2111.08543/) (2021)
- [Fair multilingual vandalism detection system for Wikipedia](https://mlsanity.com/paper/2306.01650/) (2023)
- [Graph-Linguistic Fusion: Using Language Models for Wikidata Vandalism Detection](https://mlsanity.com/paper/2505.18136/) (2025)
- [Detecting Sockpuppetry on Wikipedia Using Meta-Learning](https://mlsanity.com/paper/2506.10314/) (2025)

## Abstract (arXiv)

The aim of this study is to find key areas of research that can be useful to fight against disinformation on Wikipedia. To address this problem we perform a literature review trying to answer three main questions: (i) What is disinformation? (ii) What are the most popular mechanisms to spread online disinformation? and (iii) Which are the mechanisms that are currently being used to fight against disinformation?. In all these three questions we take first a general approach, considering studies from different areas such as journalism and communications, sociology, philosophy, information and political sciences. And comparing those studies with the current situation on the Wikipedia ecosystem. We conclude that in order to keep Wikipedia as free as possible from disinformation, it is necessary to help patrollers to early detect disinformation and assess the credibility of external sources. More research is needed to develop tools that use state-of-the-art machine learning techniques to detect potentially dangerous content, empowering patrollers to deal with attacks that are becoming more complex and sophisticated.