A Hybrid Approach to Aspect Based Sentiment Analysis Using Transfer Learning

Gaurav Negi, Rajdeep Sarkar, Omnia Zayed, Paul Buitelaar

Abstract
Aspect-Based Sentiment Analysis ( ABSA) aims to identify terms or multiword expressions (MWEs) on which sentiments are expressed and the sentiment polarities associated with them. The development of supervised models has been at the forefront of research in this area. However, training these models requires the availability of manually annotated datasets which is both expensive and time-consuming. Furthermore, the available annotated datasets are tailored to a specific domain, language, and text type. In this work, we address this notable challenge in current state-of-the-art ABSA research. We propose a hybrid approach for Aspect Based Sentiment Analysis using transfer learning. The approach focuses on generating weakly-supervised annotations by exploiting the strengths of both large language models (LLM) and traditional syntactic dependencies. We utilise syntactic dependency structures of sentences to complement the annotations generated by LLMs, as they may overlook domain-specific aspect terms. Extensive experimentation on multiple datasets is performed to demonstrate the efficacy of our hybrid method for the tasks of aspect term extraction and aspect sentiment classification.
Anthology ID:
2024.lrec-main.56
Volume:
Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)
Month:
May
Year:
2024
Address:
Torino, Italia
Editors:
Nicoletta Calzolari, Min-Yen Kan, Veronique Hoste, Alessandro Lenci, Sakriani Sakti, Nianwen Xue
Venues:
LREC | COLING
SIG:
Publisher:
ELRA and ICCL
Note:
Pages:
647–658
Language:
URL:
https://aclanthology.org/2024.lrec-main.56
DOI:
Bibkey:
Cite (ACL):
Gaurav Negi, Rajdeep Sarkar, Omnia Zayed, and Paul Buitelaar. 2024. A Hybrid Approach to Aspect Based Sentiment Analysis Using Transfer Learning. In Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024), pages 647–658, Torino, Italia. ELRA and ICCL.
Cite (Informal):
A Hybrid Approach to Aspect Based Sentiment Analysis Using Transfer Learning (Negi et al., LREC-COLING 2024)
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