A productive clash of perspectives? The interplay between articles’ and authors’ perspectives and their impact on Wikipedia edits in a controversial domain

Abstract

This study examined predictors of the development of Wikipedia articles that deal with controversial issues. We chose a corpus of articles in the German-language version of Wikipedia about alternative medicine as a representative controversial issue. We extracted edits made until March 2013 and categorized them using a supervised machine learning setup as either being pro conventional medicine, pro alternative medicine, or neutral. Based on these categories, we established relevant variables, such as the perspectives of articles and of authors at certain points in time, the (im)balance of an article’s perspective, the number of non-neutral edits per article, the number of authors per article, authors’ heterogeneity per article, and incongruity between authors’ and articles’ perspectives. The underlying objective was to predict the development of articles’ perspectives with regard to the controversial topic. The empirical part of the study is embedded in theoretical considerations about editorial biases and the effectiveness of norms and rules in Wikipedia, such as the neutral point of view policy. Our findings revealed a selection bias where authors edited mainly articles with perspectives similar to their own viewpoint. Regression analyses showed that an author’s perspective as well as the article’s previous perspectives predicted the perspective of the resulting edits, albeit both predictors interact with each other. Further analyses indicated that articles with more non-neutral edits were altogether more balanced. We also found a positive effect of the number of authors and of the authors’ heterogeneity on articles’ balance. However, while the effect of the number of authors was reserved to pro-conventional medicine articles, the authors’ heterogenity effect was restricted to pro-alternative medicine articles. Finally, we found a negative effect of incongruity between authors’ and articles’ perspectives that was pronounced for the pro-alternative medicine articles.

Using big data techniques for measuring productive friction in mass collaboration online environments

“…Knowledge dynamics in Wikipedia articles In a recent article, Jirschitzka et al (2017) devised a study based on text classification investigating the role and function of productive friction in learning and knowledge construction on the Wikipedia platform. The study focused on the struggle between proponents of alternative and conventional medicine.…”

“…Nevertheless, it still seems that productive friction between one's own views Fig. 1 Number of contributions as a function of the friction between an author's and an article's view (adapted from Jirschitzka et al 2017) and others' views is necessary for learning and successful knowledge construction. Platforms such as Wikipedia that explicitly aim at incorporating different viewpoints enable some degree of exposure to others' perspectives, which may be supportive for the development of knowledge (Oeberst et al 2014), even though it is not a guarantee for successful knowledge construction (Greenstein et al 2016;Holtz et al 2018).…”

“…Consequently, the emergence of new knowledge frequently occurs along the fault-lines of knowledge structures; in websites for collaborative knowledge construction, for example, knowledge is often developed as a consequence of experts from different domains discussing their respective ideas ). Furthermore, a certain degree of variety in terms of attitudes and knowledge seems to alleviate unwanted biases and radicalization processes in such platforms (Jirschitzka et al 2017).…”

Effects of Contributor Experience on the Quality of Health-Related Wikipedia Articles (Preprint)

“…Consulting the internet for healthrelated information has undoubtedly become a common and widespread phenomenon [6,7]. Over the last several years, Wikipedia has emerged as one of the most important knowledge resources for health-related information on the web [4,8,9]. In this paper we (1) describe potential quality issues as indicated by community applied tags in health-related Wikipedia articles, and we (2) analyze the importance of contributor experience for the quality of health-related Wikipedia articles.…”

“…Wikipedia relies heavily on social control to ensure the quality of its collaboratively constructed knowledge corpus, and Wikipedia contributors are expected and invited to correct other contributors' mistakes [9]. Controversial and conflictual issues are to be debated by the contributors until consensus is reached [10].…”