Abstract
Code-switching is commonly used in the free-form text environment, such as social media, and it is especially favored in emotion expressions. Emotions in codeswitching texts differ from monolingual texts in that they can be expressed in either monolingual or bilingual forms. In this paper, we first utilize two kinds of knowledge, i.e. bilingual and sentimental information to bridge the gap between different languages. Moreover, we use a term-document bipartite graph to incorporate both bilingual and sentimental information, and propose a label propagation based approach to learn and predict in the bipartite graph. Empirical studies demonstrate the effectiveness of our proposed approach in detecting emotion in code-switching texts.
Original language | English |
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Title of host publication | ACL-IJCNLP 2015 - 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing of the Asian Federation of Natural Language Processing, Proceedings of the Conference |
Publisher | Association for Computational Linguistics (ACL) |
Pages | 763-768 |
Number of pages | 6 |
Volume | 2 |
ISBN (Electronic) | 9781941643730 |
Publication status | Published - 1 Jan 2015 |
Event | 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing of the Asian Federation of Natural Language Processing, ACL-IJCNLP 2015 - Beijing, China Duration: 26 Jul 2015 → 31 Jul 2015 |
Conference
Conference | 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing of the Asian Federation of Natural Language Processing, ACL-IJCNLP 2015 |
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Country/Territory | China |
City | Beijing |
Period | 26/07/15 → 31/07/15 |
ASJC Scopus subject areas
- Artificial Intelligence
- Software
- Language and Linguistics
- Linguistics and Language