2017/06/23 by Benjamin Timmermans, Timmermans, Benjamin, Tobias Kuhn +5 · 1 voice
Computer Science · Social Sciences · #Computational and Text Analysis Methods #Computers and Society (cs.CY) #FOS: Computer and information sciences #Hate Speech and Cyberbullying Detection #Social Media and Politics #cs.CY
paper · pdf · doi:10.48550/arxiv.1706.07643
In Proceedings of the 9th International Conference on Social Informatics (SocInfo) 2017
openalex publication_date 2017/06/23 · arxiv published 2017/06/23 · arxiv created 2017/08/30 · arxiv updated 2017/08/31 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Climate change, vaccination, abortion, Trump: Many topics are surrounded by fierce controversies. The nature of such heated debates and their elements have been studied extensively in the social science literature. More recently, various computational approaches to controversy analysis have appeared, using new data sources such as Wikipedia, which help us now better understand these phenomena. However, compared to what social sciences have discovered about such debates, the existing computational approaches mostly focus on just a few of the many important aspects around the concept of controversies. In order to link the two strands, we provide and evaluate here a controversy model that is both, rooted in the findings of the social science literature and at the same time strongly linked to computational methods. We show how this model can lead to computational controversy analytics that have full coverage over all the crucial aspects that make up a controversy.