Mining Cross-Cultural Differences and Similarities in Social Media

Bill Yuchen Lin, Frank F. Xu, Kenny Zhu, Seung-won Hwang


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
Venue:
ACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
709–719
Language:
URL:
https://www.aclweb.org/anthology/P18-1066
DOI:
10.18653/v1/P18-1066
Bib Export formats:
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PDF:
http://aclanthology.lst.uni-saarland.de/P18-1066.pdf
Poster:
 P18-1066.Poster.pdf