The Sentiment Problem: A Critical Survey towards Deconstructing Sentiment Analysis

Pranav Venkit, Mukund Srinath, Sanjana Gautam, Saranya Venkatraman, Vipul Gupta, Rebecca Passonneau, Shomir Wilson


Abstract
We conduct an inquiry into the sociotechnical aspects of sentiment analysis (SA) by critically examining 189 peer-reviewed papers on their applications, models, and datasets. Our investigation stems from the recognition that SA has become an integral component of diverse sociotechnical systems, exerting influence on both social and technical users. By delving into sociological and technological literature on sentiment, we unveil distinct conceptualizations of this term in domains such as finance, government, and medicine. Our study exposes a lack of explicit definitions and frameworks for characterizing sentiment, resulting in potential challenges and biases. To tackle this issue, we propose an ethics sheet encompassing critical inquiries to guide practitioners in ensuring equitable utilization of SA. Our findings underscore the significance of adopting an interdisciplinary approach to defining sentiment in SA and offer a pragmatic solution for its implementation.
Anthology ID:
2023.emnlp-main.848
Volume:
Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing
Month:
December
Year:
2023
Address:
Singapore
Editors:
Houda Bouamor, Juan Pino, Kalika Bali
Venue:
EMNLP
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
13743–13763
Language:
URL:
https://aclanthology.org/2023.emnlp-main.848
DOI:
10.18653/v1/2023.emnlp-main.848
Bibkey:
Cite (ACL):
Pranav Venkit, Mukund Srinath, Sanjana Gautam, Saranya Venkatraman, Vipul Gupta, Rebecca Passonneau, and Shomir Wilson. 2023. The Sentiment Problem: A Critical Survey towards Deconstructing Sentiment Analysis. In Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, pages 13743–13763, Singapore. Association for Computational Linguistics.
Cite (Informal):
The Sentiment Problem: A Critical Survey towards Deconstructing Sentiment Analysis (Venkit et al., EMNLP 2023)
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PDF:
https://aclanthology.org/2023.emnlp-main.848.pdf
Video:
 https://aclanthology.org/2023.emnlp-main.848.mp4