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        <title>Recognizing Humour using Word Associations and Humour Anchor Extraction</title>
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            <namePart type="given">Emily</namePart>
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    <abstract>This paper attempts to marry the interpretability of statistical machine learning approaches with the more robust models of joke structure and joke semantics capable of being learned by neural models. Specifically, we explore the use of semantic relatedness features based on word associations, rather than the more common Word2Vec similarity, on a binary humour identification task and identify several factors that make word associations a better fit for humour. We also explore the effects of using joke structure, in the form of humour anchors (Yang et al., 2015), for improving the performance of semantic features and show that, while an intriguing idea, humour anchors contain several pitfalls that can hurt performance.</abstract>
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%0 Conference Proceedings
%T Recognizing Humour using Word Associations and Humour Anchor Extraction
%A Cattle, Andrew
%A Ma, Xiaojuan
%Y Bender, Emily M.
%Y Derczynski, Leon
%Y Isabelle, Pierre
%S Proceedings of the 27th International Conference on Computational Linguistics
%D 2018
%8 August
%I Association for Computational Linguistics
%C Santa Fe, New Mexico, USA
%F cattle-ma-2018-recognizing
%X This paper attempts to marry the interpretability of statistical machine learning approaches with the more robust models of joke structure and joke semantics capable of being learned by neural models. Specifically, we explore the use of semantic relatedness features based on word associations, rather than the more common Word2Vec similarity, on a binary humour identification task and identify several factors that make word associations a better fit for humour. We also explore the effects of using joke structure, in the form of humour anchors (Yang et al., 2015), for improving the performance of semantic features and show that, while an intriguing idea, humour anchors contain several pitfalls that can hurt performance.
%U https://aclanthology.org/C18-1157
%P 1849-1858

Markdown (Informal)

[Recognizing Humour using Word Associations and Humour Anchor Extraction](https://aclanthology.org/C18-1157) (Cattle & Ma, COLING 2018)

• Recognizing Humour using Word Associations and Humour Anchor Extraction (Cattle & Ma, COLING 2018)

ACL

• Andrew Cattle and Xiaojuan Ma. 2018. Recognizing Humour using Word Associations and Humour Anchor Extraction. In Proceedings of the 27th International Conference on Computational Linguistics, pages 1849–1858, Santa Fe, New Mexico, USA. Association for Computational Linguistics.