@inproceedings{khatri-p-2020-sarcasm,
    title = "Sarcasm Detection in Tweets with {BERT} and {G}lo{V}e Embeddings",
    author = "Khatri, Akshay  and
      P, Pranav",
    editor = "Klebanov, Beata Beigman  and
      Shutova, Ekaterina  and
      Lichtenstein, Patricia  and
      Muresan, Smaranda  and
      Wee, Chee  and
      Feldman, Anna  and
      Ghosh, Debanjan",
    booktitle = "Proceedings of the Second Workshop on Figurative Language Processing",
    month = jul,
    year = "2020",
    address = "Online",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/jlcl-multiple-ingestion/2020.figlang-1.7/",
    doi = "10.18653/v1/2020.figlang-1.7",
    pages = "56--60",
    abstract = "Sarcasm is a form of communication in which the person states opposite of what he actually means. 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 all of the context provided in the dataset to which the user is reacting along with his actual response."
}