Climate change is one of the greatest threats to humanity, and yet society is unable to agree on its existence, causes and mitigation actions. This controversy in society manifests in all areas of public life including online channels. Wikipedia serves as a source of information not just for individuals, but also for search engines and artificial intelligence. Studying the climate change controversy on Wikipedia could provide insights that help to understand the controversy, and bolster the efforts in finding are solution for the controversy.

With this aim, the edit histories of 86 pages related to climate change, their talk pages, as well as three baselines pages and their talk pages were collected from the English language Wikipedia, and analysed using Python for data extraction, manipulation and formatting, and R for data processing and analysis, data visualisation and significance testing.

The statistical analyses of the different traces in the edit histories revealed interesting patterns of expression of the controversy. In addition, the statistical analyses hinted at several differences in the ways that editors on controversial pages differ from editors on non-controversial pages, thus showing an effect of controversy on Wikipedia and its culture .A detailed examination of the climate change pages showed that the controversy in Wikipedia traces affects the metadata of articles, thus identifying such articles to the casual reader. The novel method used in this study identified several new indicators of controversy.