Sarcasm detection in tweets with BERT and GloVe embeddings

Abstract

Sarcasm is a form of communication in which the person states opposite of what he actually means. It is ambiguous in nature. In this paper, we propose using machine learning techniques with BERT and GloVe embeddings to detect sarcasm in tweets. The dataset is preprocessed before extracting the embeddings. The proposed model also uses the context in which the user is reacting to along with his actual response. © 2020 Association for Computational Linguistics.