USING N-GRAMS TO IDENTIFY EDIT WARS ON WIKIPEDIA (original) (raw)
Related papers
2011
Abstract We present a new, efficient method for automatically detecting severe conflicts,edit wars' in Wikipedia and evaluate this method on six different language Wikipedias. We discuss how the number of edits and reverts deviate in such pages from those following the general workflow, and argue that earlier work has significantly over-estimated the contentiousness of the Wikipedia editing process.
Characterization and prediction of Wikipedia edit wars
2011
We present a new, efficient method for automatically detecting conflict cases and test it on five different language Wikipedias. We discuss how the number of edits, reverts, the length of discussions deviate in such pages from those following the general workflow.
Dynamics of Edit War Sequences in Wikipedia
2020
In any collaborative system, cooperation and conflicts exist together. While in some cases these conflicts improve the output, they also lead to increased overhead. This requires examining the dynamics of these conflicts with the help of underlying data. In Wikipedia articles, the conflicts are captured by edit wars which may be examined through the revision history of these articles. In this work, we perform a systematic analysis of the conflicts present in 1,208 controversial articles of Wikipedia captured in the form of edit war sequences. We examine various key characteristics of these sequences and further use them to estimate the outcome of the edit wars. The study indicates the possibility of devising automated coordination mechanisms for handling conflicts in collaborative spaces.
The dynamic nature of conflict in Wikipedia
EPL (Europhysics Letters), 2014
The voluntary process of Wikipedia edition provides an environment where the outcome is clearly a collective product of interactions involving a large number of people. We propose a simple agent-based model, developed from real data, to reproduce the collaborative process of Wikipedia edition. With a small number of simple ingredients, our model mimics several interesting features of real human behaviour, namely in the context of edit wars. We show that the level of conflict is determined by a tolerance parameter, which measures the editors' capability to accept different opinions and to change their own opinion. We propose to measure conflict with a parameter based on mutual reverts, which increases only in contentious situations. Using this parameter, we find a distribution for the inter-peace periods that is heavy-tailed. The effects of wiki-robots in the conflict levels and in the edition patterns are also studied. Our findings are compared with previous parameters used to measure conflicts in edit wars.
Societal Controversies in Wikipedia Articles
CHI'15: 33rd Annual ACM Conference on Human Factors in Computing Systems Proceedings, 2015
Collaborative content creation inevitably reaches situations where different points of view lead to conflict. We focus on Wikipedia, the free encyclopedia anyone may edit, where disputes about content in controversial articles often reflect larger societal debates. While Wikipedia has a public edit history and discussion section for every article, the substance of these sections is difficult to phantom for Wikipedia users interested in the development of an article and in locating which topics were most controversial. In this paper we present Contropedia, a tool that augments Wikipedia articles and gives insight into the development of controversial topics. Contropedia uses an efficient language agnostic measure based on the edit history that focuses on wiki links to easily identify which topics within a Wikipedia article have been most controversial and when.
The Most Controversial Topics in Wikipedia: A Multilingual and Geographical Analysis
SSRN Journal
We present, visualize and analyse the similarities and differences between the controversial topics related to "edit wars" identified in 10 different language versions of Wikipedia. After a brief review of the related work we describe the methods developed to locate, measure, and categorize the controversial topics in the different languages. Visualizations of the degree of overlap between the top 100 list of most controversial articles in different languages and the content related geographical locations will be presented. We discuss what the presented analysis and visualizations can tell us about the multicultural aspects of Wikipedia, and, in general, about cultures of peer-production with focus on universal and specifically, local features. We demonstrate that Wikipedia is more than just an encyclopaedia; it is also a window into divergent social-spatial priorities, interests and preferences.
Creating, destroying, and restoring value in Wikipedia
Proceedings of the …, 2007
Wikipedia's brilliance and curse is that any user can edit any of the encyclopedia entries. We introduce the notion of the impact of an edit, measured by the number of times the edited version is viewed. Using several datasets, including recent logs of all article views, we show that frequent editors dominate what people see when they visit Wikipedia, and that this domination is increasing. * Similarly, using the same impact measure, we show that the probability of a typical article view being damaged is small but increasing, and we present empirically grounded classes of damage. Finally, we make policy recommendations for Wikipedia and other wikis in light of these findings.
Dynamics of conflicts in Wikipedia
2012
In this work we study the dynamical features of editorial wars in Wikipedia (WP). Based on our previously established algorithm, we build up samples of controversial and peaceful articles and analyze the temporal characteristics of the activity in these samples. On short time scales, we show that there is a clear correspondence between conflict and burstiness of activity patterns, and that memory effects play an important role in controversies.
Companion Proceedings of The 2019 World Wide Web Conference on - WWW '19, 2019
Wikipedia serves as a good example of how editors collaborate to form and maintain an article. The relationship between editors, derived from their sequence of editing activity, results in a directed network structure called the revision network, that potentially holds valuable insights into editing activity. In this paper we create revision networks to assess differences between controversial and non-controversial articles, as labelled by Wikipedia. Originating from complex networks, we apply motif analysis, which determines the under or over-representation of induced sub-structures, in this case triads of editors. We analyse 21,631 Wikipedia articles in this way, and use principal component analysis to consider the relationship between their motif subgraph ratio profiles. Results show that a small number of induced triads play an important role in characterising relationships between editors, with controversial articles having a tendency to cluster. This provides useful insight into editing behaviour and interaction capturing counter-narratives, without recourse to semantic analysis. It also provides a potentially useful feature for future prediction of controversial Wikipedia articles.