Sarcasm Detection in Tweets with BERT and GloVe Embeddings

Akshay Khatri, Pranav P


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.
Anthology ID:
2020.figlang-1.7
Volume:
Proceedings of the Second Workshop on Figurative Language Processing
Month:
July
Year:
2020
Address:
Online
Editors:
Beata Beigman Klebanov, Ekaterina Shutova, Patricia Lichtenstein, Smaranda Muresan, Chee Wee, Anna Feldman, Debanjan Ghosh
Venue:
Fig-Lang
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
56–60
Language:
URL:
https://aclanthology.org/2020.figlang-1.7
DOI:
10.18653/v1/2020.figlang-1.7
Bibkey:
Cite (ACL):
Akshay Khatri and Pranav P. 2020. Sarcasm Detection in Tweets with BERT and GloVe Embeddings. In Proceedings of the Second Workshop on Figurative Language Processing, pages 56–60, Online. Association for Computational Linguistics.
Cite (Informal):
Sarcasm Detection in Tweets with BERT and GloVe Embeddings (Khatri & P, Fig-Lang 2020)
Copy Citation:
PDF:
https://aclanthology.org/2020.figlang-1.7.pdf
Video:
 http://slideslive.com/38929697