Zhu, Lixing, Fang, Zheng, Pergola, Gabriele, Procter, Rob and He, Yulan (2022) Disentangled learning of stance and aspect topics for vaccine attitude detection in social media. In: 2022 Conference of the North American Chapter of the Association for Computational Linguistics, Seattle, United States, 10–15 Jul 2022. Published in: Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics pp. 1566-1580. doi:10.18653/v1/2022.naacl-main.112

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Abstract

Building models to detect vaccine attitudes on social media is challenging because of the composite, often intricate aspects involved, and the limited availability of annotated data. Existing approaches have relied heavily on supervised training that requires abundant annotations and pre-defined aspect categories. Instead, with the aim of leveraging the large amount of unannotated data now available on vaccination, we propose a novel semi-supervised approach for vaccine attitude detection, called VADet. A variational autoencoding architecture based on language models is employed to learn from unlabelled data the topical information of the domain. Then, the model is fine-tuned with a few manually annotated examples of user attitudes. We validate the effectiveness of VADet on our annotated data and also on an existing vaccination corpus annotated with opinions on vaccines. Our results show that VADet is able to learn disentangled stance and aspect topics, and outperforms existing aspect-based sentiment analysis models on both stance detection and tweet clustering.

Item Type:	Conference Item (Paper)
Divisions:	Faculty of Science, Engineering and Medicine > Science > Computer Science
Journal or Publication Title:	Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics
Publisher:	Association for Computational Linguistics
Place of Publication:	Seattle, United States
Official Date:	10 July 2022
Dates:	Date Event 10 July 2022 Published
Page Range:	pp. 1566-1580
DOI:	10.18653/v1/2022.naacl-main.112
Status:	Peer Reviewed
Publication Status:	Published
Access rights to Published version:	Open Access (Creative Commons)
Copyright Holders:	Association for Computational Linguistics
Date of first compliant deposit:	25 October 2022
Date of first compliant Open Access:	25 October 2022
Funder:	EPSRC, University of Warwick, UKRI
Is Part Of:	1
Conference Paper Type:	Paper
Title of Event:	2022 Conference of the North American Chapter of the Association for Computational Linguistics
Type of Event:	Conference
Location of Event:	Seattle, United States
Date(s) of Event:	10–15 Jul 2022
Open Access Version:	ArXiv

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