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        <title>Crossing the Line: Where do Demographic Variables Fit into Humor Detection?</title>
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    <abstract>Recent humor classification shared tasks have struggled with two issues: either the data comprises a highly constrained genre of humor which does not broadly represent humor, or the data is so indiscriminate that the inter-annotator agreement on its humor content is drastically low. These tasks typically average over all annotators’ judgments, in spite of the fact that humor is a highly subjective phenomenon. We argue that demographic factors influence whether a text is perceived as humorous or not. We propose the addition of demographic information about the humor annotators in order to bin ratings more sensibly. We also suggest the addition of an ‘offensive’ label to distinguish between different generations, in terms of humor. This would allow for more nuanced shared tasks and could lead to better performance on downstream tasks, such as content moderation.</abstract>
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%0 Conference Proceedings
%T Crossing the Line: Where do Demographic Variables Fit into Humor Detection?
%A Meaney, J. A.
%Y Rijhwani, Shruti
%Y Liu, Jiangming
%Y Wang, Yizhong
%Y Dror, Rotem
%S Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics: Student Research Workshop
%D 2020
%8 July
%I Association for Computational Linguistics
%C Online
%F meaney-2020-crossing
%X Recent humor classification shared tasks have struggled with two issues: either the data comprises a highly constrained genre of humor which does not broadly represent humor, or the data is so indiscriminate that the inter-annotator agreement on its humor content is drastically low. These tasks typically average over all annotators’ judgments, in spite of the fact that humor is a highly subjective phenomenon. We argue that demographic factors influence whether a text is perceived as humorous or not. We propose the addition of demographic information about the humor annotators in order to bin ratings more sensibly. We also suggest the addition of an ‘offensive’ label to distinguish between different generations, in terms of humor. This would allow for more nuanced shared tasks and could lead to better performance on downstream tasks, such as content moderation.
%R 10.18653/v1/2020.acl-srw.24
%U https://aclanthology.org/2020.acl-srw.24
%U https://doi.org/10.18653/v1/2020.acl-srw.24
%P 176-181

Markdown (Informal)

[Crossing the Line: Where do Demographic Variables Fit into Humor Detection?](https://aclanthology.org/2020.acl-srw.24) (Meaney, ACL 2020)

• Crossing the Line: Where do Demographic Variables Fit into Humor Detection? (Meaney, ACL 2020)

ACL

• J. A. Meaney. 2020. Crossing the Line: Where do Demographic Variables Fit into Humor Detection?. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics: Student Research Workshop, pages 176–181, Online. Association for Computational Linguistics.