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Investigating the saliency of sentiment expressions in aspect-based sentiment analysis

Wagner, Joachim orcid logoORCID: 0000-0002-8290-3849 and Foster, Jennifer orcid logoORCID: 0000-0002-7789-4853 (2023) Investigating the saliency of sentiment expressions in aspect-based sentiment analysis. In: Findings of the Association for Computational Linguistics: ACL 2023, 10-12 July 2023, Toronto, Canada.

Abstract
We examine the behaviour of an aspect-based sentiment classifier built by fine-tuning the BERT BASE model on the SemEval 2016 English dataset. In a set of masking experiments, we examine the extent to which the tokens identified as salient by LIME and a gradient-based method are being used by the classifier. We find that both methods are able to produce faithful rationales, with LIME outperforming the gradient-based method. We also identify a set of manually annotated sentiment expressions for this dataset, and carry out more masking experiments with these as human rationales. The enhanced performance of a classifier that only sees the relevant sentiment expressions suggests that they are not being used to their full potential. A comparison of the LIME and gradient rationales with the sentiment expressions reveals only a moderate level of agreement. Some disagreements are related to the fixed length of the rationales and the tendency of the rationales to contain content words related to the aspect itself.
Metadata
Item Type:Conference or Workshop Item (Poster)
Event Type:Conference
Refereed:Yes
Subjects:Computer Science > Computational linguistics
DCU Faculties and Centres:DCU Faculties and Schools > Faculty of Engineering and Computing > School of Computing
Research Initiatives and Centres > ADAPT
Published in: Findings of the Association for Computational Linguistics: ACL 2023. . Association for Computational Linguistics.
Publisher:Association for Computational Linguistics
Official URL:https://doi.org/10.18653/v1/2023.findings-acl.807
Copyright Information:© 2023 Association for Computational Linguistics
Funders:Science Foundation Ireland
ID Code:29138
Deposited On:18 Oct 2023 12:24 by Jennifer Foster . Last Modified 18 Oct 2023 12:24
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