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Does Commonsense help in detecting Sarcasm?

Authors :
Chowdhury, Somnath Basu Roy
Chaturvedi, Snigdha
Source :
Proceedings of the Second Workshop on Insights from Negative Results in NLP.
Publication Year :
2021
Publisher :
Association for Computational Linguistics, 2021.

Abstract

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.<br />Comment: Accepted at Insights from Negative Results in NLP Workshop, EMNLP 2021

Details

Database :
OpenAIRE
Journal :
Proceedings of the Second Workshop on Insights from Negative Results in NLP
Accession number :
edsair.doi.dedup.....b09186273bbc3e18d98bb2621e60457b