This paper summarises the differences and similarities found between humans and three natural language processing models when attempting to identify whether English online comments are sarcastic or not. Three models were used to analyse 300 comments from the FigLang 2020 Reddit Dataset, with and without context. The same 300 comments were also given to 39 non-native speakers of English and the results were compared. The aim was to find whether there were any results that could be applied to English as a Foreign Language (EFL) teaching. The results showed that there were similarities between the models and non-native speakers, in particular the logistic regression model. They also highlighted weaknesses with both non-native speakers and the models in detecting sarcasm when the comments included political topics or were phrased as questions. This has potential implications for how the EFL teaching industry could implement the results of error analysis of NLP models in teaching practices.

This is a research proposal for doctoral research into sarcasm detection, and the real-time compilation of an English language corpus of sarcastic utterances. It details the previous research into similar topics, the potential research directions and the research aims.