Dynamics of Conflicts in Wikipedia

Citation: Yasseri T, Sumi R, Rung A, Kornai A, Kertesz J ( Dynamics of Conflicts in Wikipedia Taha Yasseri 0 Robert Sumi 0 Andra s Rung 0 Andra s Kornai 0 Ja nos Kerte sz 0 Attila Szolnoki, Hungarian Academy of Sciences, Hungary 0 1 Department of Theoretical Physics, Budapest University of Technology and Economics, Budapest, Hungary, 2 Computer and Automation Research Institute, Hungarian Academy of Sciences , Budapest , Hungary 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. On long time scales, we identify three distinct developmental patterns for the overall behavior of the articles. We are able to distinguish cases eventually leading to consensus from those cases where a compromise is far from achievable. Finally, we analyze discussion networks and conclude that edit wars are mainly fought by few editors only. - New media such as the internet and the web enable entirely new ways of collaboration, opening unprecedented opportunities for handling tasks of extraordinary size and complexity. Such collaborative schemes have already been used to solve challenges in software engineering [1] and mathematics [2]. Understanding the laws of internet-based collaborative value production is of great importance. Perhaps the most prominent example of such value production is Wikipedia (WP), a free, collaborative, multilingual internet encyclopedia [3]. WP evolves without the supervision of a preselected expert team, its voluntary editors define the rules and maintain the quality. WP has grown beyond other encyclopedias both in size and in use, having unquestionably become the number one reference in practice. Although criticism has been continuously expressed concerning its reliability and accuracy, partly because the editorial policy is in favor of consensus over credentials [4], independent studies have shown that, as early as in 2005, science articles in WP and Encyclopedia Britannica were of comparable quality [5]. As every edit and discussion post is saved and available, WP is particularly well suited to study internetbased collaborative processes. Indeed, WP has been studied extensively from different aspects including the growth of content and community [6,7], coverage [8,9] and evolution of the hyperlink networks [1014], the extraction of semantic networks [1517], linguistic studies [1820], user reputation [21] and collaboration quality [22,23], vandalism detection [2426], and the social aspects of the editor community [2732]. Usually, different editors constructively extend each others text, correct minor errors and mistakes until a consensual article emerges this is the most natural, and by far the most common, way for a WP entry to be developed [33]. Good examples include (WP articles will be cited in typewriter font throughout the text) Benjamin Franklin, Pumpkin or Helium. As we shall see, in the English WP close to 99% of the articles result from this rather smooth, constructive process. However, the development of WP articles is not always peaceful and collaborative, there are sometimes heavy fights called edit wars between groups representing opposing opinions. Schneider et al. [34] estimated that in the English WP, among the highly edited or highly viewed articles (these notions are strongly correlated, see [35]), about 12% of discussions are devoted to reverts and vandalism, suggesting that the WP development process for articles of major interest is highly contentious. The WP community has created a full system of measures to resolve conflict situations, including the so called three revert rule (see Wikipedia:Edit warring), locking articles for non-registered editors, tagging controversial articles, and temporal or final banning of malevolent editors. It is against this rich backdrop of explicit rules, explicit or implicit regulations, and unwritten conventions that the present paper undertakes to investigate a fundamental part of the collaborative value production, how conflicts emerge and get resolved. The first order of business is to construct an automated procedure to identify controversial articles. For a human reader the simplest way to do so is to go to the discussion (talk) pages of the articles, which often show the typical signatures of conflicts as known from social psychology [36]. The length of the discussion page could already be considered a good indicator of conflict: the more severe the conflict, the longer the talk page is expected to be (this will be shown in detail later). However, this feature is very language dependent: while conflicts are indeed fought out in detail on discussion pages in the English WP, German editors do not use this vehicle for the same purpose. Moreover, there are WPs, e.g. the Hungarian one, where discussion pages are always rather sparse, rarely mentioning the actual arguments. Clearly the discussion page alone is not an appropriate source to identify conflicts if we aim at a general, multi-lingual, culture-independent indicator. Figure 1. Revert and mutual revert maps of Benjamin Franklin (left) and Israel and the apartheid analogy (right). Diagrams in upper row show the map of all reverts, whereas only mutual reverts are depicted on the diagrams in the lower row. Nr and Nd are the number of edits made by the reverting and reverted editors respectively. Size of the dots is proportional to the number of reverts by the same reverting and reverted pair of editors. doi:10.1371/journal.pone.0038869.g001 Conflicts in WP were studied previously both on the article and on the user level. Kittur et al. [37,38] and Vuong et al. [39] measured controversiality by counting the controversial tag in the history of an article, and compared other possible metrics to that. It should be noted, however, that this is at best a one-sided measure as highly disputed pages such as Gdansk or Euthanasia in the English WP lack such tags, and the situation is even worse in other WPs. In [38], different page metrics like the number of reverts, the number of revisions etc. were compared to the tag counts and in [39] the number of deleted words between users were counted and a Mutual Reinforcement Principle [40] was used to measure how controversial a given article is. Clearly, there are several features of an article which correlate with its controversiality, making it highly non-trivial to choose an appropriate indicator. Some papers try to detect the negative conflict links between WP editors in a given article and, based on this, attempt to classify editors into groups. The main idea of the method used by Kittur et al. [38] is to relate (...truncated)