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CSenticNet: A Concept-Level Resource for Sentiment Analysis in Chinese Language

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Computational Linguistics and Intelligent Text Processing (CICLing 2017)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10762))

Abstract

In recent years, sentiment analysis has become a hot topic in natural language processing. Although sentiment analysis research in English is rather mature, Chinese sentiment analysis has just set sail, as the limited amount of sentiment resources in Chinese severely limits its development. In this paper, we present a method for the construction of a Chinese sentiment resource. We utilize both English sentiment resources and the Chinese knowledge base NTU Multi-lingual Corpus. In particular, we first propose a resource based on SentiWordNet and a second version based on SenticNet.

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Notes

  1. 1.

    http://compling.hss.ntu.edu.sg/ntumc/.

  2. 2.

    http://searchforum.org.cn/tansongbo/corpus/ChnSentiCorp_htl_ba_2000.rar.

  3. 3.

    http://product.it168.com.

  4. 4.

    NLP&CC is an annual conference of Chinese information technology professional committee organized by Chinese computer Federation (CCF). More details are available at http://tcci.ccf.org.cn/conference/2013/index.html.

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Authors and Affiliations

  1. School of Computer Science and Engineering, Nanyang Technological University, Singapore, Singapore

    Haiyun Peng & Erik Cambria

Authors
  1. Haiyun Peng
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  2. Erik Cambria
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Corresponding author

Correspondence to Haiyun Peng .

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Editors and Affiliations

  1. CIC, Instituto Politécnico Nacional, Mexico City, Mexico

    Alexander Gelbukh

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Peng, H., Cambria, E. (2018). CSenticNet: A Concept-Level Resource for Sentiment Analysis in Chinese Language. In: Gelbukh, A. (eds) Computational Linguistics and Intelligent Text Processing. CICLing 2017. Lecture Notes in Computer Science(), vol 10762. Springer, Cham. https://doi.org/10.1007/978-3-319-77116-8_7

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  • DOI: https://doi.org/10.1007/978-3-319-77116-8_7

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-77115-1

  • Online ISBN: 978-3-319-77116-8

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