TalkUp: Paving the Way for Understanding Empowering Language

Lucille Njoo, Chan Park, Octavia Stappart, Marvin Thielk, Yi Chu, Yulia Tsvetkov

Abstract
Empowering language is important in many real-world contexts, from education to workplace dynamics to healthcare. Though language technologies are growing more prevalent in these contexts, empowerment has seldom been studied in NLP, and moreover, it is inherently challenging to operationalize because of its implicit nature. This work builds from linguistic and social psychology literature to explore what characterizes empowering language. We then crowdsource a novel dataset of Reddit posts labeled for empowerment, reasons why these posts are empowering to readers, and the social relationships between posters and readers. Our preliminary analyses show that this dataset, which we call TalkUp, can be used to train language models that capture empowering and disempowering language. More broadly, TalkUp provides an avenue to explore implication, presuppositions, and how social context influences the meaning of language.
Anthology ID:
2023.findings-emnlp.625
Volume:
Findings of the Association for Computational Linguistics: EMNLP 2023
Month:
December
Year:
2023
Address:
Singapore
Editors:
Houda Bouamor, Juan Pino, Kalika Bali
Venue:
Findings
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
9334–9354
Language:
URL:
https://aclanthology.org/2023.findings-emnlp.625
DOI:
10.18653/v1/2023.findings-emnlp.625
Bibkey:
Cite (ACL):
Lucille Njoo, Chan Park, Octavia Stappart, Marvin Thielk, Yi Chu, and Yulia Tsvetkov. 2023. TalkUp: Paving the Way for Understanding Empowering Language. In Findings of the Association for Computational Linguistics: EMNLP 2023, pages 9334–9354, Singapore. Association for Computational Linguistics.
Cite (Informal):
TalkUp: Paving the Way for Understanding Empowering Language (Njoo et al., Findings 2023)
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PDF:
https://preview.aclanthology.org/nschneid-patch-4/2023.findings-emnlp.625.pdf
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