Abstract
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.
Highlights
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
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]
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 [10,11,12,13,14], the extraction of semantic networks [15,16,17], linguistic studies [18,19,20], user reputation [21] and collaboration quality [22,23], vandalism detection [24,25,26], and the social aspects of the editor community [27,28,29,30,31,32]
Summary
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 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 [10,11,12,13,14], the extraction of semantic networks [15,16,17], linguistic studies [18,19,20], user reputation [21] and collaboration quality [22,23], vandalism detection [24,25,26], and the social aspects of the editor community [27,28,29,30,31,32]
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