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        <title>A Cancel Culture Corpus through the Lens of Natural Language Processing</title>
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            <title>Proceedings of the First Workshop on Language Technology and Resources for a Fair, Inclusive, and Safe Society within the 13th Language Resources and Evaluation Conference</title>
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            <namePart type="given">Kolawole</namePart>
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    <abstract>Cancel Culture as an Internet phenomenon has been previously explored from a social and legal science perspective. This paper demonstrates how Natural Language Processing tasks can be derived from this previous work, underlying techniques on how cancel culture can be measured, identified and evaluated. As part of this paper, we introduce a first cancel culture data set with of over 2.3 million tweets and a framework to enlarge it further. We provide a detailed analysis of this data set and propose a set of features, based on various models including sentiment analysis and emotion detection that can help characterizing cancel culture.</abstract>
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%0 Conference Proceedings
%T A Cancel Culture Corpus through the Lens of Natural Language Processing
%A Erker, Justus-Jonas
%A Goanta, Catalina
%A Spanakis, Gerasimos
%Y Adebayo, Kolawole
%Y Nanda, Rohan
%Y Verma, Kanishk
%Y Davis, Brian
%S Proceedings of the First Workshop on Language Technology and Resources for a Fair, Inclusive, and Safe Society within the 13th Language Resources and Evaluation Conference
%D 2022
%8 June
%I European Language Resources Association
%C Marseille, France
%F erker-etal-2022-cancel
%X Cancel Culture as an Internet phenomenon has been previously explored from a social and legal science perspective. This paper demonstrates how Natural Language Processing tasks can be derived from this previous work, underlying techniques on how cancel culture can be measured, identified and evaluated. As part of this paper, we introduce a first cancel culture data set with of over 2.3 million tweets and a framework to enlarge it further. We provide a detailed analysis of this data set and propose a set of features, based on various models including sentiment analysis and emotion detection that can help characterizing cancel culture.
%U https://aclanthology.org/2022.lateraisse-1.3/
%P 17-25

Markdown (Informal)

[A Cancel Culture Corpus through the Lens of Natural Language Processing](https://aclanthology.org/2022.lateraisse-1.3/) (Erker et al., LATERAISSE 2022)

• A Cancel Culture Corpus through the Lens of Natural Language Processing (Erker et al., LATERAISSE 2022)

ACL

• Justus-Jonas Erker, Catalina Goanta, and Gerasimos Spanakis. 2022. A Cancel Culture Corpus through the Lens of Natural Language Processing. In Proceedings of the First Workshop on Language Technology and Resources for a Fair, Inclusive, and Safe Society within the 13th Language Resources and Evaluation Conference, pages 17–25, Marseille, France. European Language Resources Association.