BERT’s The Word : Sarcasm Target Detection using BERT

Pradeesh Parameswaran, Andrew Trotman, Veronica Liesaputra, David Eyers


Abstract
In 2019, the Australasian Language Technology Association (ALTA) organised a shared task to detect the target of sarcastic comments posted on social media. However, there were no winners as it proved to be a difficult task. In this work, we revisit the task posted by ALTA by using transformers, specifically BERT, given the current success of the transformer-based model in various NLP tasks. We conducted our experiments on two BERT models (TD-BERT and BERT-AEN). We evaluated our model on the data set provided by ALTA (Reddit) and two additional data sets: ‘book snippets’ and ‘Tweets’. Our results show that our proposed method achieves a 15.2% improvement from the current state-of-the-art system on the Reddit data set and 4% improvement on Tweets.
Anthology ID:
2021.alta-1.21
Volume:
Proceedings of the The 19th Annual Workshop of the Australasian Language Technology Association
Month:
December
Year:
2021
Address:
Online
Venue:
ALTA
SIG:
Publisher:
Australasian Language Technology Association
Note:
Pages:
185–191
Language:
URL:
https://aclanthology.org/2021.alta-1.21
DOI:
Bibkey:
Cite (ACL):
Pradeesh Parameswaran, Andrew Trotman, Veronica Liesaputra, and David Eyers. 2021. BERT’s The Word : Sarcasm Target Detection using BERT. In Proceedings of the The 19th Annual Workshop of the Australasian Language Technology Association, pages 185–191, Online. Australasian Language Technology Association.
Cite (Informal):
BERT’s The Word : Sarcasm Target Detection using BERT (Parameswaran et al., ALTA 2021)
Copy Citation:
PDF:
https://aclanthology.org/2021.alta-1.21.pdf