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        <title>Can Contextualizing User Embeddings Improve Sarcasm and Hate Speech Detection?</title>
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            <namePart type="given">David</namePart>
            <namePart type="family">Bamman</namePart>
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            <namePart type="given">Katherine</namePart>
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        <name type="personal">
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    <abstract>While implicit embeddings so far have been mostly concerned with creating an overall representation of the user, we evaluate a different approach. By only considering content directed at a specific topic, we create sub-user embeddings, and measure their usefulness on the tasks of sarcasm and hate speech detection. In doing so, we show that task-related topics can have a noticeable effect on model performance, especially when dealing with intended expressions like sarcasm, but less so for hate speech, which is usually labelled as such on the receiving end.</abstract>
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%0 Conference Proceedings
%T Can Contextualizing User Embeddings Improve Sarcasm and Hate Speech Detection?
%A Breitwieser, Kim
%Y Bamman, David
%Y Hovy, Dirk
%Y Jurgens, David
%Y Keith, Katherine
%Y O’Connor, Brendan
%Y Volkova, Svitlana
%S Proceedings of the Fifth Workshop on Natural Language Processing and Computational Social Science (NLP+CSS)
%D 2022
%8 November
%I Association for Computational Linguistics
%C Abu Dhabi, UAE
%F breitwieser-2022-contextualizing
%X While implicit embeddings so far have been mostly concerned with creating an overall representation of the user, we evaluate a different approach. By only considering content directed at a specific topic, we create sub-user embeddings, and measure their usefulness on the tasks of sarcasm and hate speech detection. In doing so, we show that task-related topics can have a noticeable effect on model performance, especially when dealing with intended expressions like sarcasm, but less so for hate speech, which is usually labelled as such on the receiving end.
%R 10.18653/v1/2022.nlpcss-1.14
%U https://aclanthology.org/2022.nlpcss-1.14/
%U https://doi.org/10.18653/v1/2022.nlpcss-1.14
%P 126-139

Markdown (Informal)

[Can Contextualizing User Embeddings Improve Sarcasm and Hate Speech Detection?](https://aclanthology.org/2022.nlpcss-1.14/) (Breitwieser, NLP+CSS 2022)

• Can Contextualizing User Embeddings Improve Sarcasm and Hate Speech Detection? (Breitwieser, NLP+CSS 2022)

ACL

• Kim Breitwieser. 2022. Can Contextualizing User Embeddings Improve Sarcasm and Hate Speech Detection?. In Proceedings of the Fifth Workshop on Natural Language Processing and Computational Social Science (NLP+CSS), pages 126–139, Abu Dhabi, UAE. Association for Computational Linguistics.