Leveraging Writing Systems Change for Deep Learning Based Chinese Emotion Analysis

Rong Xiang, Yunfei Long, Qin Lu, Dan Xiong, I-Hsuan Chen

Abstract
Social media text written in Chinese communities contains mixed scripts including major text written in Chinese, an ideograph-based writing system, and some minor text using Latin letters, an alphabet-based writing system. This phenomenon is called writing systems changes (WSCs). Past studies have shown that WSCs can be used to express emotions, particularly where the social and political environment is more conservative. However, because WSCs can break the syntax of the major text, it poses more challenges in Natural Language Processing (NLP) tasks like emotion classification. In this work, we present a novel deep learning based method to include WSCs as an effective feature for emotion analysis. The method first identifies all WSCs points. Then representation of the major text is learned through an LSTM model whereas the minor text is learned by a separate CNN model. Emotions in the minor text are further highlighted through an attention mechanism before emotion classification. Performance evaluation shows that incorporating WSCs features using deep learning models can improve performance measured by F1-scores compared to the state-of-the-art model.
Anthology ID:
W18-6214
Volume:
Proceedings of the 9th Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis
Month:
October
Year:
2018
Address:
Brussels, Belgium
Editors:
Alexandra Balahur, Saif M. Mohammad, Veronique Hoste, Roman Klinger
Venue:
WASSA
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
91–96
Language:
URL:
https://aclanthology.org/W18-6214
DOI:
10.18653/v1/W18-6214
Bibkey:
Cite (ACL):
Rong Xiang, Yunfei Long, Qin Lu, Dan Xiong, and I-Hsuan Chen. 2018. Leveraging Writing Systems Change for Deep Learning Based Chinese Emotion Analysis. In Proceedings of the 9th Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis, pages 91–96, Brussels, Belgium. Association for Computational Linguistics.
Cite (Informal):
Leveraging Writing Systems Change for Deep Learning Based Chinese Emotion Analysis (Xiang et al., WASSA 2018)
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PDF:
https://preview.aclanthology.org/ml4al-ingestion/W18-6214.pdf
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