Abstract
Cross-cultural differences and similarities are common in cross-lingual natural language understanding, especially for research in social media. For instance, people of distinct cultures often hold different opinions on a single named entity. Also, understanding slang terms across languages requires knowledge of cross-cultural similarities. In this paper, we study the problem of computing such cross-cultural differences and similarities. We present a lightweight yet effective approach, and evaluate it on two novel tasks: 1) mining cross-cultural differences of named entities and 2) finding similar terms for slang across languages. Experimental results show that our framework substantially outperforms a number of baseline methods on both tasks. The framework could be useful for machine translation applications and research in computational social science.- Anthology ID:
- P18-1066
- Volume:
- Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
- Month:
- July
- Year:
- 2018
- Address:
- Melbourne, Australia
- Editors:
- Iryna Gurevych, Yusuke Miyao
- Venue:
- ACL
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 709–719
- Language:
- URL:
- https://aclanthology.org/P18-1066
- DOI:
- 10.18653/v1/P18-1066
- Cite (ACL):
- Bill Yuchen Lin, Frank F. Xu, Kenny Zhu, and Seung-won Hwang. 2018. Mining Cross-Cultural Differences and Similarities in Social Media. In Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 709–719, Melbourne, Australia. Association for Computational Linguistics.
- Cite (Informal):
- Mining Cross-Cultural Differences and Similarities in Social Media (Lin et al., ACL 2018)
- PDF:
- https://preview.aclanthology.org/add_acl24_videos/P18-1066.pdf