Aspect-Based Emotion Analysis and Multimodal Coreference: A Case Study of Customer Comments on Adidas Instagram Posts

Luna De Bruyne, Akbar Karimi, Orphee De Clercq, Andrea Prati, Veronique Hoste


Abstract
While aspect-based sentiment analysis of user-generated content has received a lot of attention in the past years, emotion detection at the aspect level has been relatively unexplored. Moreover, given the rise of more visual content on social media platforms, we want to meet the ever-growing share of multimodal content. In this paper, we present a multimodal dataset for Aspect-Based Emotion Analysis (ABEA). Additionally, we take the first steps in investigating the utility of multimodal coreference resolution in an ABEA framework. The presented dataset consists of 4,900 comments on 175 images and is annotated with aspect and emotion categories and the emotional dimensions of valence and arousal. Our preliminary experiments suggest that ABEA does not benefit from multimodal coreference resolution, and that aspect and emotion classification only requires textual information. However, when more specific information about the aspects is desired, image recognition could be essential.
Anthology ID:
2022.lrec-1.61
Volume:
Proceedings of the Thirteenth Language Resources and Evaluation Conference
Month:
June
Year:
2022
Address:
Marseille, France
Venue:
LREC
SIG:
Publisher:
European Language Resources Association
Note:
Pages:
574–580
Language:
URL:
https://aclanthology.org/2022.lrec-1.61
DOI:
Bibkey:
Cite (ACL):
Luna De Bruyne, Akbar Karimi, Orphee De Clercq, Andrea Prati, and Veronique Hoste. 2022. Aspect-Based Emotion Analysis and Multimodal Coreference: A Case Study of Customer Comments on Adidas Instagram Posts. In Proceedings of the Thirteenth Language Resources and Evaluation Conference, pages 574–580, Marseille, France. European Language Resources Association.
Cite (Informal):
Aspect-Based Emotion Analysis and Multimodal Coreference: A Case Study of Customer Comments on Adidas Instagram Posts (De Bruyne et al., LREC 2022)
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PDF:
https://aclanthology.org/2022.lrec-1.61.pdf