2020 · 31 citations · 17 references
ComputingComputer ScienceComputational LinguisticsNatural Language ProcessingSocial Media AnalyticsConversational User InterfacesDialogue SystemsLanguage ModelingOpinion MiningSemantic NetworksSocial Media
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.
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Fastai: A Layered API for Deep Learning
Jeremy Howard, Sylvain Gugger · Information · 2020 · 1K citations · Full text
Sarcasm as Contrast between a Positive Sentiment and Negative Situation
Ellen Riloff, Ashequl Qadir, Prafulla Surve et al. · 2013 · 591 citations · Full text