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        <title>Identifying Distributional Perspectives from Colingual Groups</title>
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    <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</abstract>
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%0 Conference Proceedings
%T Identifying Distributional Perspectives from Colingual Groups
%A Tian, Yufei
%A Chakrabarty, Tuhin
%A Morstatter, Fred
%A Peng, Nanyun
%Y Ku, Lun-Wei
%Y Li, Cheng-Te
%S Proceedings of the Ninth International Workshop on Natural Language Processing for Social Media
%D 2021
%8 June
%I Association for Computational Linguistics
%C Online
%F tian-etal-2021-identifying
%X 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
%R 10.18653/v1/2021.socialnlp-1.16
%U https://aclanthology.org/2021.socialnlp-1.16
%U https://doi.org/10.18653/v1/2021.socialnlp-1.16
%P 178-190

Markdown (Informal)

[Identifying Distributional Perspectives from Colingual Groups](https://aclanthology.org/2021.socialnlp-1.16) (Tian et al., SocialNLP 2021)

• Identifying Distributional Perspectives from Colingual Groups (Tian et al., SocialNLP 2021)

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.