@inproceedings{venkit-etal-2023-sentiment,
title = "The Sentiment Problem: A Critical Survey towards Deconstructing Sentiment Analysis",
author = "Venkit, Pranav and
Srinath, Mukund and
Gautam, Sanjana and
Venkatraman, Saranya and
Gupta, Vipul and
Passonneau, Rebecca and
Wilson, Shomir",
editor = "Bouamor, Houda and
Pino, Juan and
Bali, Kalika",
booktitle = "Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing",
month = dec,
year = "2023",
address = "Singapore",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2023.emnlp-main.848",
doi = "10.18653/v1/2023.emnlp-main.848",
pages = "13743--13763",
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.",
}
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%0 Conference Proceedings
%T The Sentiment Problem: A Critical Survey towards Deconstructing Sentiment Analysis
%A Venkit, Pranav
%A Srinath, Mukund
%A Gautam, Sanjana
%A Venkatraman, Saranya
%A Gupta, Vipul
%A Passonneau, Rebecca
%A Wilson, Shomir
%Y Bouamor, Houda
%Y Pino, Juan
%Y Bali, Kalika
%S Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing
%D 2023
%8 December
%I Association for Computational Linguistics
%C Singapore
%F venkit-etal-2023-sentiment
%X 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.
%R 10.18653/v1/2023.emnlp-main.848
%U https://aclanthology.org/2023.emnlp-main.848
%U https://doi.org/10.18653/v1/2023.emnlp-main.848
%P 13743-13763
Markdown (Informal)
[The Sentiment Problem: A Critical Survey towards Deconstructing Sentiment Analysis](https://aclanthology.org/2023.emnlp-main.848) (Venkit et al., EMNLP 2023)
ACL