Facilitating Opinion Diversity through Hybrid NLP Approaches

Michiel Van Der Meer


Abstract
Modern democracies face a critical issue of declining citizen participation in decision-making. Online discussion forums are an important avenue for enhancing citizen participation. This thesis proposal 1) identifies the challenges involved in facilitating large-scale online discussions with Natural Language Processing (NLP), 2) suggests solutions to these challenges by incorporating hybrid human-AI technologies, and 3) investigates what these technologies can reveal about individual perspectives in online discussions. We propose a three-layered hierarchy for representing perspectives that can be obtained by a mixture of human intelligence and large language models. We illustrate how these representations can draw insights into the diversity of perspectives and allow us to investigate interactions in online discussions.
Anthology ID:
2024.naacl-srw.29
Volume:
Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 4: Student Research Workshop)
Month:
June
Year:
2024
Address:
Mexico City, Mexico
Editors:
Yang (Trista) Cao, Isabel Papadimitriou, Anaelia Ovalle, Marcos Zampieri, Francis Ferraro, Swabha Swayamdipta
Venue:
NAACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
272–284
Language:
URL:
https://aclanthology.org/2024.naacl-srw.29
DOI:
10.18653/v1/2024.naacl-srw.29
Bibkey:
Cite (ACL):
Michiel Van Der Meer. 2024. Facilitating Opinion Diversity through Hybrid NLP Approaches. In Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 4: Student Research Workshop), pages 272–284, Mexico City, Mexico. Association for Computational Linguistics.
Cite (Informal):
Facilitating Opinion Diversity through Hybrid NLP Approaches (Van Der Meer, NAACL 2024)
Copy Citation:
PDF:
https://aclanthology.org/2024.naacl-srw.29.pdf