Publication | Open Access
Transformers on Sarcasm Detection with Context
27
Citations
11
References
2020
Year
Unknown Venue
EngineeringCommunicationMultimodal Sentiment AnalysisSentiment AnalysisLanguage ProcessingText MiningNatural Language ProcessingSocial MediaComputational LinguisticsAffective ComputingLanguage EngineeringConversation AnalysisContent AnalysisMachine TranslationNlp TaskLanguage TechnologyConversation ContextSarcasm DetectionParalinguisticsArtsHumor DetectionLinguistics
Sarcasm Detection with Context, a shared task of Second Workshop on Figurative Language Processing (co-located with ACL 2020), is study of effect of context on Sarcasm detection in conversations of Social media. We present different techniques and models, mostly based on transformer for Sarcasm Detection with Context. We extended latest pre-trained transformers like BERT, RoBERTa, spanBERT on different task objectives like single sentence classification, sentence pair classification, etc. to understand role of conversation context for sarcasm detection on Twitter conversations and conversation threads from Reddit. We also present our own architecture consisting of LSTM and Transformers to achieve the objective.
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