Amit Kumar Jena author Aman Sinha author Rohit Agarwal author 2020-jul text Association for Computational Linguistics Online conference publication 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 on CodaLab and achieved 75.0% F1-score on the Twitter dataset and 66.3% F1-score on Reddit dataset. kumar-jena-etal-2020-c https://www.aclweb.org/anthology/2020.figlang-1.8 2020-jul 61 66