Identifying Distributional Perspectives from Colingual Groups

Yufei Tian, Tuhin Chakrabarty, Fred Morstatter, Nanyun Peng


Abstract
Discrepancies exist among different cultures or languages. A lack of mutual understanding among different colingual groups about the perspectives on specific values or events may lead to uninformed decisions or biased opinions. Thus, automatically understanding the group perspectives can provide essential back-ground for many natural language processing tasks. In this paper, we study colingual groups and use language corpora as a proxy to identify their distributional perspectives. We present a novel computational approach to learn shared understandings, and benchmark our method by building culturally-aware models for the English, Chinese, and Japanese languages. Ona held out set of diverse topics, including marriage, corruption, democracy, etc., our model achieves high correlation with human judgements regarding intra-group values and inter-group differences
Anthology ID:
2021.socialnlp-1.16
Volume:
Proceedings of the Ninth International Workshop on Natural Language Processing for Social Media
Month:
June
Year:
2021
Address:
Online
Venues:
NAACL | SocialNLP
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
178–190
Language:
URL:
https://aclanthology.org/2021.socialnlp-1.16
DOI:
10.18653/v1/2021.socialnlp-1.16
Bibkey:
Cite (ACL):
Yufei Tian, Tuhin Chakrabarty, Fred Morstatter, and Nanyun Peng. 2021. Identifying Distributional Perspectives from Colingual Groups. In Proceedings of the Ninth International Workshop on Natural Language Processing for Social Media, pages 178–190, Online. Association for Computational Linguistics.
Cite (Informal):
Identifying Distributional Perspectives from Colingual Groups (Tian et al., SocialNLP 2021)
Copy Citation:
PDF:
https://aclanthology.org/2021.socialnlp-1.16.pdf