2024 COLING COLING 2024

Error Analysis of NLP Models and Non-Native Speakers of English Identifying Sarcasm in Reddit Comments

Abstract

AbstractThis 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.

🧭 Keyword Pioneer — nlp model evaluation
🐝 Cross-Pollinator — Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Security & Privacy, Speech & Audio