Abstract
Previous researches have placed emphasis on analyzing emotions in monolingual text, neglecting the fact that emotions are often found in bilingual or code-switching posts in social media. Traditional methods for the identification or classification of emotion fail to accommodate the code-switching content. To address this challenge, in this paper, we propose a multi-view learning framework to learn and detect the emotions through both monolingual and bilingual views. In particular, the monolingual views are extracted from the monolingual text separately, and the bilingual view is constructed with both monolingual and translated text collectively. Empirical studies demonstrate the effectiveness of our proposed approach in detecting emotions in code-switching texts.
Original language | English |
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Title of host publication | Proceedings of 2015 International Conference on Asian Language Processing, IALP 2015 |
Publisher | IEEE |
Pages | 90-93 |
Number of pages | 4 |
ISBN (Electronic) | 9781467395953 |
DOIs | |
Publication status | Published - 12 Apr 2016 |
Event | International Conference on Asian Language Processing, IALP 2015 - Suzhou, China Duration: 24 Oct 2015 → 25 Oct 2015 |
Conference
Conference | International Conference on Asian Language Processing, IALP 2015 |
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Country/Territory | China |
City | Suzhou |
Period | 24/10/15 → 25/10/15 |
Keywords
- code-switching
- emotion analysis
- multi-view learning
ASJC Scopus subject areas
- Linguistics and Language
- Artificial Intelligence
- Computer Vision and Pattern Recognition
- Signal Processing