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- W4286972002 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." @default.
- W4286972002 created "2022-07-25" @default.
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- W4286972002 date "2021-09-17" @default.
- W4286972002 modified "2023-09-26" @default.
- W4286972002 title "Does Commonsense help in detecting Sarcasm?" @default.
- W4286972002 doi "https://doi.org/10.48550/arxiv.2109.08588" @default.
- W4286972002 hasPublicationYear "2021" @default.
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