While historically computational humor paid very little attention to sociology and mostly took into account subparts of linguistics and some psychology, Christie Davies wrote a number of papers that should affect the study of computational humor directly. This paper will look at one paper to illustrate this point, namely Christie’s chapter in the Primer of Humor Research. With the advancements in computational processing and big data analysis/analytics, it is becoming possible to look at a large collection of humorous texts that are available on the web. In particular, older texts, including joke materials, that are being scanned from previously published printed versions. Most of the approaches within computational humor concentrated on comparison of present/existing jokes, without taking into account classes of jokes that are absent in a given setting. While the absence of a class is unlikely to affect classification – something that researchers in computational humor seem to be interested in – it does come into light when features of various classes are compared and conclusions are being made. This paper will describe existing approaches and how they could be enhanced, thanks to Davies’s contributions and the advancements in data processing.
Hobbs, J. R. (2009). ‘Word meaning and world knowledge’, in Maienborn, C., von Heusinger, K., Portner, P. & van Leusen, N. (eds.), Semantics: An International Handbook of Natural Language Meaning, The Hague: Mouton de Gruyter, pp. 740–761..
Miller, T., Hempelmann, C. F., & Gurevych, I. (2017). ‘SemEval 2017 Task 7: Detection and interpretation of English puns’, Proceedings of the 11th International Workshop on Semantic Evaluation (SemEval-2017), pp. 56–68.
Raskin, V. (1985). Semantic Mechanisms of Humor. Dordrecht: D. Reidel.
Ritchie, G. (2001). ‘Current directions in computational humour’, Artificial Intelligence Review 16 (2), pp. 119–135.
Taylor, J. M. (2017). ‘Computational treatments of humor’, in Attardo, S. (ed.), The Routledge Handbook of Language and Humor, New York, NY: Routledge.