| Summary: | 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.
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