A bilingual attention network for code-switched emotion prediction

Zhongqing Wang, Yue Zhang, Sophia Yat Mei Lee, Shoushan Li, Guodong Zhou

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

26 Citations (Scopus)

Abstract

Emotions in code-switching text can be expressed in either monolingual or bilingual forms. However, relatively little research has placed emphasis on code-switching text. The challenges of this task include the exploration both monolingual and bilingual information of each post and capturing the informative words from the code-switching context. To address these challenges, we propose a Bilingual Attention Network (BAN) model to aggregate the monolingual and bilingual informative words to form vectors from the document representation, and integrate the attention vectors to predict the emotion. The experiments show the effectiveness of the proposed model. Visualization of the attention layers illustrates that the model selects informative words qualitatively.

Original languageEnglish
Title of host publicationCOLING 2016 - 26th International Conference on Computational Linguistics, Proceedings of COLING 2016
Subtitle of host publicationTechnical Papers
PublisherAssociation for Computational Linguistics, ACL Anthology
Pages1624-1634
Number of pages11
ISBN (Print)9784879747020
Publication statusPublished - 1 Jan 2016
Event26th International Conference on Computational Linguistics, COLING 2016 - Osaka, Japan
Duration: 11 Dec 201616 Dec 2016

Publication series

NameCOLING 2016 - 26th International Conference on Computational Linguistics, Proceedings of COLING 2016: Technical Papers

Conference

Conference26th International Conference on Computational Linguistics, COLING 2016
Country/TerritoryJapan
CityOsaka
Period11/12/1616/12/16

ASJC Scopus subject areas

  • Computational Theory and Mathematics
  • Language and Linguistics
  • Linguistics and Language

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