From Toxicity in Online Comments to Incivility in American News: Proceed with Caution

Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics, pages 2620–2630 April 19 - 23, 2021. ©2021 Association for Computational Linguistics 2620 From Toxicity in Online Comments to Incivility in American News: Proceed with Caution Anushree Hede Oshin Agarwal Linda Lu Diana C. Mutz Ani Nenkova University of Pennsylvania {anuhede,oagarwal,lulinda,nenkova}@seas.upenn.edu mutz@upenn.edu Abstract The ability to quantify incivility online, in news and in congressional debates, is of great interest to political scientists. Computational tools for detecting online incivility for English are now fairly accessible and potentially could be applied more broadly. We test the Jigsaw Perspective API for its ability to detect the degree of incivility on a corpus that we de- veloped, consisting of manual annotations of civility in American news. We demonstrate that toxicity models, as exemplified by Per- spective, are inadequate for the analysis of in- civility in news. We carry out error analysis that points to the need to develop methods to remove spurious correlations between words often mentioned in the news, especially iden- tity descriptors and incivility. Without such improvements, applying Perspective or similar models on news is likely to lead to wrong con- clusions, that are not aligned with the human perception of incivility. 1 Introduction Surveys of public opinion report that most Amer- icans think that the tone and nature of political debate in this country have become more nega- tive and less respectful and that the heated rhetoric by politicians raises the risk for violence (Cen- ter, 2019). These observations motivate the need to study (in)civility in political discourse in all spheres of interaction, including online (Ziegele et al., 2018; Jaidka et al., 2019), in congressional debates (Uslaner, 2000) and as presented in news (Meltzer, 2015; Rowe, 2015). Accurate automated means for coding incivility could facilitate this re- search, and political scientists have already turned to using off-the-shelf computational tools for study- ing civility (Frimer and Skitka, 2018; Jaidka et al., 2019; Theocharis et al., 2020). Computational tools however, have been devel- oped for different purposes, focusing on detecting language in online forums that violate community norms. The goal of these applications is to support human moderators by promptly focusing their at- tention on likely problematic posts. When studying civility in political discourse, it is primarily of inter- est to characterize the overall civility of interactions in a given source (i.e., news programs) or domain (i.e., congressional debates), as an average over a period of interest. Applying off-the-shelf tools for toxicity detection is appealingly convenient, but such use has not been validated for any domain, while uses in support of moderation efforts have been validated only for online comments. We examine the feasibility of quantifying inci- vility in the news via the Jigsaw Perspective API, which has been trained on over a million online comments rated for toxicity and deployed in sev- eral scenarios to support moderator effort online1. We collect human judgments of the (in)civility in one month worth of three American news programs. We show …

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