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    <titleInfo>
        <title>Mining Cross-Cultural Differences and Similarities in Social Media</title>
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    <name type="personal">
        <namePart type="given">Seung-won</namePart>
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    <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.</abstract>
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%0 Conference Proceedings
%T Mining Cross-Cultural Differences and Similarities in Social Media
%A Lin, Bill Yuchen
%A Xu, Frank F.
%A Zhu, Kenny
%A Hwang, Seung-won
%Y Gurevych, Iryna
%Y Miyao, Yusuke
%S Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
%D 2018
%8 July
%I Association for Computational Linguistics
%C Melbourne, Australia
%F lin-etal-2018-mining
%X 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.
%R 10.18653/v1/P18-1066
%U https://aclanthology.org/P18-1066
%U https://doi.org/10.18653/v1/P18-1066
%P 709-719

Markdown (Informal)

[Mining Cross-Cultural Differences and Similarities in Social Media](https://aclanthology.org/P18-1066) (Lin et al., ACL 2018)

• Mining Cross-Cultural Differences and Similarities in Social Media (Lin et al., ACL 2018)

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.