'Are you having a laugh?': detecting humorous expressions on social media: an exploration of theory, current approaches and future work

Suzanne Elayan, Martin Sykora, Thomas W. Jackson and Ejovwoke Onojeharho

International Journal of Information Technology and Management, 2022, vol. 21, issue 1, 115-137

Abstract: The role of humorous content on social media has rarely been taken into account in prior work. Understanding its dynamics on social media provides insight that could benefit a range of applications in sentiment analysis. This paper introduces literature on humour theory, related human behaviour and a discussion of existing automated approaches to humour detection. We present and review current research on humorous language use on social media and its significance. In particular, example humorous expressions from Twitter are used to illustrate the heterogeneous types of humour on social media. Since most prior work focused on English language contexts, the analysed example uses of humour are set in the Arabic cultural context, providing a novel view. The primary contribution of this paper is the position that similar to sentiment analysis, automated humour detection in its own right has potential in understanding public reactions and should be explored in future studies.

Keywords: humour; social media; Twitter; sentiment analysis; natural language processing; data mining; automated humour detection; computational linguistics; social media analytics. (search for similar items in EconPapers)
Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:ids:ijitma:v:21:y:2022:i:1:p:115-137

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