Papers › Does Commonsense help in detecting Sarcasm?

Does Commonsense help in detecting Sarcasm?

17 Sep 2021EMNLP (insights) 2021 11arXiv:2109.08588archive 2025-07-28

Somnath Basu Roy Chowdhury, Snigdha Chaturvedi

Sarcasm detection is important for several NLP tasks such as sentiment identification in product reviews, user feedback, and online forums. It is a challenging task requiring a deep understanding of language, context, and world knowledge. In this paper, we investigate whether incorporating commonsense knowledge helps in sarcasm detection. For this, we incorporate commonsense knowledge into the prediction process using a graph convolution network with pre-trained language model embeddings as input. Our experiments with three sarcasm detection datasets indicate that the approach does not outperform the baseline model. We perform an exhaustive set of experiments to analyze where commonsense support adds value and where it hurts classification. Our implementation is publicly available at: https://github.com/brcsomnath/commonsense-sarcasm.

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Language ModelingLanguage ModellingSarcasm DetectionWorld Knowledge

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Convolution

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