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Title: Multi-view learning for emotion detection in code-switching texts
Authors: Lee, SYM 
Wang, Z 
Issue Date: 2016
Source: International Conference on Asian Language Processing, IALP 2015, Suzhou, China, 24 - 25 October 2015, 7451539, p. 90-93
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.
Keywords: Code-switching
Emotion analysis
Multi-view learning
Publisher: Institute of Electrical and Electronics Engineers
ISBN: 9781467395953
DOI: 10.1109/IALP.2015.7451539
Appears in Collections:Conference Paper

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