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Proceedings of the Second Workshop on Figurative Language Processing
Automatic Sarcasm Detection in conversations is a difficult and tricky task. Classifying an utterance as sarcastic or not in isolation can be futile since most of the time the sarcastic nature of a sentence heavily relies on its context. This paper presents our proposed model, C-Net, which takes contextual information of a sentence in a sequential manner to classify it as sarcastic or non-sarcastic. Our model showcases competitive performance in the Sarcasm Detection shared task organised ondoi:10.18653/v1/2020.figlang-1.8 fatcat:yr4sxj4jrra3lmrqbbp4tjczd4