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        <title>Assessing Cognitive Linguistic Influences in the Assignment of Blame</title>
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            <title>Proceedings of the Ninth International Workshop on Natural Language Processing for Social Media</title>
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    <abstract>Lab studies in cognition and the psychology of morality have proposed some thematic and linguistic factors that influence moral reasoning. This paper assesses how well the findings of these studies generalize to a large corpus of over 22,000 descriptions of fraught situations posted to a dedicated forum. At this social-media site, users judge whether or not an author is in the wrong with respect to the event that the author described. We find that, consistent with lab studies, there are statistically significant differences in uses of first-person passive voice, as well as first-person agents and patients, between descriptions of situations that receive different blame judgments. These features also aid performance in the task of predicting the eventual collective verdicts.</abstract>
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%0 Conference Proceedings
%T Assessing Cognitive Linguistic Influences in the Assignment of Blame
%A Zhou, Karen
%A Smith, Ana
%A Lee, Lillian
%Y Ku, Lun-Wei
%Y Li, Cheng-Te
%S Proceedings of the Ninth International Workshop on Natural Language Processing for Social Media
%D 2021
%8 June
%I Association for Computational Linguistics
%C Online
%F zhou-etal-2021-assessing
%X Lab studies in cognition and the psychology of morality have proposed some thematic and linguistic factors that influence moral reasoning. This paper assesses how well the findings of these studies generalize to a large corpus of over 22,000 descriptions of fraught situations posted to a dedicated forum. At this social-media site, users judge whether or not an author is in the wrong with respect to the event that the author described. We find that, consistent with lab studies, there are statistically significant differences in uses of first-person passive voice, as well as first-person agents and patients, between descriptions of situations that receive different blame judgments. These features also aid performance in the task of predicting the eventual collective verdicts.
%R 10.18653/v1/2021.socialnlp-1.5
%U https://aclanthology.org/2021.socialnlp-1.5
%U https://doi.org/10.18653/v1/2021.socialnlp-1.5
%P 61-69

Markdown (Informal)

[Assessing Cognitive Linguistic Influences in the Assignment of Blame](https://aclanthology.org/2021.socialnlp-1.5) (Zhou et al., SocialNLP 2021)

• Assessing Cognitive Linguistic Influences in the Assignment of Blame (Zhou et al., SocialNLP 2021)

ACL

• Karen Zhou, Ana Smith, and Lillian Lee. 2021. Assessing Cognitive Linguistic Influences in the Assignment of Blame. In Proceedings of the Ninth International Workshop on Natural Language Processing for Social Media, pages 61–69, Online. Association for Computational Linguistics.