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Online antisocial behavior, such as cyberbullying, harassment, and trolling, is a widespread problem that threatens free discussion and has negative physical and mental health consequences for victims and communities. While prior work has proposed automated methods to identify hostile comments in online discussions, these methods work retrospectively on comments that have already been posted, making it difficult to intervene before an interaction escalates. In this paper we instead consider the problem of forecasting future hostilities in online discussions, which we decompose into two tasks: (1) given an initial sequence of non-hostile comments in a discussion, predict whether some future comment will contain hostility; and (2) given the first hostile comment in a discussion, predict whether this will lead to an escalation of hostility in subsequent comments. Thus, we aim to forecast both the presence and intensity of hostile comments based on linguistic and social features from earlier comments. To evaluate our approach, we introduce a corpus of over 30K annotated Instagram comments from over 1,100 posts. Our approach is able to predict the appearance of a hostile comment on an Instagram post ten or more hours in the future with an AUC of .82 (task 1), and can furthermore distinguish between high and low levels of future hostility with an AUC of .91 (task 2).

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Eskine, Kacinik, and Prinz’s (2011) influential experiment demonstrated that gustatory disgust triggers a heightened sense of moral wrongness. We report a large-scale multi-site direct replication of this study conducted by participants in the Collaborative Replications and Education Project. Participants in each sample were randomly assigned to one of three beverage conditions: bitter/disgusting, control, or sweet. Then, participants made a series of judgments indicating the moral wrongness of the behavior depicted in each of six vignettes. In the original study (N = 57), drinking the bitter beverage led to higher ratings of moral wrongness than drinking the control and sweet beverages; a beverage contrast was significant among conservative (N = 19) but not liberal (N = 25) participants. In this report, random effects meta-analyses across all participants (N = 1,137 in k = 11 studies), conservative participants (N = 142, k = 5), and liberal participants (N = 635, k = 9) revealed standardized effect sizes that were smaller than reported in the original study. Some were in the opposite of the predicted direction, all had 95% confidence intervals containing zero, and most were smaller than the effect size the original authors could meaningfully detect. In linear mixed-effects regressions, drinking the bitter beverage led to higher ratings of moral wrongness than drinking the control beverage but not the sweet beverage. Bayes Factor tests reveal greater relative support for the null hypothesis. The overall pattern provides little to no support for the theory that physical disgust via taste perception harshens judgments of moral wrongness.

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