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A growing body of research focuses on computationally detecting controversialtopics and understanding the stances people hold on them. Yet gaps remain inour theoretical and practical understanding of how to define controversy, howit manifests, and how to measure it. In this paper, we introduce a novelmeasure we call "contention", defined with respect to a topic and a population.We model contention from a mathematical standpoint. We validate our model byexamining a diverse set of sources: real-world polling data sets, actual voterdata, and Twitter coverage on several topics. In our publicly-released Twitterdata set of nearly 100M tweets, we examine several topics such as Brexit, the2016 U.S. Elections, and "The Dress", and cross-reference them with othersources. We demonstrate that the contention measure holds explanatory power fora wide variety of observed phenomena, such as controversies over climate changeand other topics that are well within scientific consensus. Finally, were-examine the notion of controversy, and present a theoretical framework thatdefines it in terms of population. We present preliminary evidence suggestingthat contention is one dimension of controversy, along with others, such as"importance". Our new contention measure, along with the hypothesized model ofcontroversy, suggest several avenues for future work in this emerginginterdisciplinary research area.

Is Climate Change Controversial? Modeling Controversy as Contention Within Populations