CASIA OpenIR  > 数字内容技术与服务研究中心  > 听觉模型与认知计算
Constructing a Chinese Conversation Corpus for Sentiment Analysis
Zhou, Yujun1,2,3; Li, Changliang1; Xu, Bo1; Xu, Jiaming1; Yang, Lei1,2,3; Xu, Bo1
Conference Namethe Sixth Conference on Natural Language Processing and Chinese Computing (NLPCC)
Conference DateNovember 8-12, 2017
Conference PlaceDalian, China
AbstractSentiment analysis plays an important role in many applications. This paper introduces our ongoing work related to the sentiment analysis on Chinese conversation. The main purpose is to construct a Chinese conversation corpus for sentiment analysis and provide a benchmark result on this corpus. To explore the effectiveness of machine learning based approaches for sentiment analysis on Chinese conversation,we firstly collected conversational data from some online English learning websites and our instant messages, and manually annotated it with three sentiment polarities and 22 fine-grained emotion classes. Then we applied multiple representative classification methods to evaluate the corpus. The evaluation results provide good suggestions for the future research. And we will release the corpus with gold standards publicly for research purposes.
KeywordChinese Conversation Short Text Sentiment Analysis Machine Learning Deep Neural Networks
Indexed ByEI
Document Type会议论文
Corresponding AuthorLi, Changliang
Affiliation1.Institute of Automation, Chinese Academy of Sciences
2.University of Chinese Academy of Sciences
3.Jiangsu Jinling Science and Technology Group Co., Ltd, Nanjing
Recommended Citation
GB/T 7714
Zhou, Yujun,Li, Changliang,Xu, Bo,et al. Constructing a Chinese Conversation Corpus for Sentiment Analysis[C],2017.
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