Ryan L Boyd
2024
From Text to Context: Contextualizing Language with Humans, Groups, and Communities for Socially Aware NLP
Adithya V Ganesan
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Siddharth Mangalik
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Vasudha Varadarajan
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Nikita Soni
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Swanie Juhng
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João Sedoc
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H. Andrew Schwartz
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Salvatore Giorgi
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Ryan L Boyd
Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 5: Tutorial Abstracts)
Aimed at the NLP researchers or practitioners who would like to integrate human - individual, group, or societal level factors into their analyses, this tutorial will cover recent techniques and libraries for doing so at each level of analysis. Starting with human-centered techniques that provide benefit to traditional document- or word-level NLP tasks (Garten et al., 2019; Lynn et al., 2017), we undertake a thorough exploration of critical human-level aspects as they pertain to NLP, gradually moving up to higher levels of analysis: individual persons, individual with agent (chat/dialogue), groups of people, and finally communities or societies.
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Co-authors
- Adithya V Ganesan 1
- Siddharth Mangalik 1
- Vasudha Varadarajan 1
- Nikita Soni 1
- Swanie Juhng 1
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