Detecting Cross-Cultural Differences Using a Multilingual Topic Model
E.D. Gutiérrez, Ekaterina Shutova, Patricia Lichtenstein, Gerard de Melo, Luca Gilardi
Abstract
Understanding cross-cultural differences has important implications for world affairs and many aspects of the life of society. Yet, the majority of text-mining methods to date focus on the analysis of monolingual texts. In contrast, we present a statistical model that simultaneously learns a set of common topics from multilingual, non-parallel data and automatically discovers the differences in perspectives on these topics across linguistic communities. We perform a behavioural evaluation of a subset of the differences identified by our model in English and Spanish to investigate their psychological validity.- Anthology ID:
- Q16-1004
- Volume:
- Transactions of the Association for Computational Linguistics, Volume 4
- Month:
- Year:
- 2016
- Address:
- Cambridge, MA
- Editors:
- Lillian Lee, Mark Johnson, Kristina Toutanova
- Venue:
- TACL
- SIG:
- Publisher:
- MIT Press
- Note:
- Pages:
- 47–60
- Language:
- URL:
- https://aclanthology.org/Q16-1004
- DOI:
- 10.1162/tacl_a_00082
- Cite (ACL):
- E.D. Gutiérrez, Ekaterina Shutova, Patricia Lichtenstein, Gerard de Melo, and Luca Gilardi. 2016. Detecting Cross-Cultural Differences Using a Multilingual Topic Model. Transactions of the Association for Computational Linguistics, 4:47–60.
- Cite (Informal):
- Detecting Cross-Cultural Differences Using a Multilingual Topic Model (Gutiérrez et al., TACL 2016)
- PDF:
- https://preview.aclanthology.org/emnlp22-frontmatter/Q16-1004.pdf