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Learning from context: A mutual reinforcement model for Chinese microblog opinion retrieval

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Abstract

This study addresses the problem of Chinese microblog opinion retrieval, which aims to retrieve opinionated Chinese microblog posts relevant to a target specified by a user query. Existing studies have shown that lexicon-based approaches employed online public sentiment resources to rank sentimentwords relying on the document features. However, this approach could not be effectively applied to microblogs that have typical user-generated content with valuable contextual information: “user–user” interpersonal interactions and “user–post/comment” intrapersonal interactions. This contextual information is very helpful in estimating the strength of sentiment words more accurately. In this study, we integrate the social contextual relationships among users, posts/comments, and sentiment words into a mutual reinforcement model and propose a unified three-layer heterogeneous graph, on which a random walk sentiment word weighting algorithm is presented to measure the strength of opinion of the sentiment words. Furthermore, the weights of sentiment words are incorporated into a lexicon-based model for Chinese microblog opinion retrieval. Comparative experiments are conducted on a Chinese microblog corpus, and the results show that our proposed mutual reinforcement model achieves significant improvement over previous methods.

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Acknowledgments

This work was partially supported by the National Natural Science Foundation of China (Grant No. 61300105), the Research Fund for Doctoral Program of Higher Education of China (2012351410010), the Key Laboratory of Network Data Science & Technology, Chinese Science and Technology Foundation (CASNDST20140X), the Key Project of Science and Technology of Fujian (2013H6012), the Project of Science and Technology of Fuzhou (2012-G-113 and 2013-PT-45), and the Scientific Research Project of the Educational Department in Fujian Province (JA10055).

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Authors and Affiliations

  1. College of Mathematics and Computer Science, Fuzhou University, Fuzhou, 350108, China

    Jingjing Wei, Xiangwen Liao, Houdong Zheng & Guolong Chen

  2. College of Electronics and Information Science, Fujian Jiangxia University, Fuzhou, 350108, China

    Jingjing Wei

  3. Fujian Provincial Key Laboratory of Network Computing and Intelligence Processing, Fuzhou University, Fuzhou, 350108, China

    Jingjing Wei, Xiangwen Liao, Houdong Zheng & Guolong Chen

  4. Institute of Computing Technology, Chinese Academic of Sciences, Beijing, 100190, China

    Xueqi Cheng

Authors
  1. Jingjing Wei
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  2. Xiangwen Liao
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  3. Houdong Zheng
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  4. Guolong Chen
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  5. Xueqi Cheng
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Corresponding author

Correspondence to Xiangwen Liao.

Additional information

Jingjing Wei is currently an assistant professor at Fujian Jiangxia University, China. She received her PhD degree from Fuzhou University, China in 2017. Her research interests include natural language processing, information retrieval and extraction, and social media analysis.

Xiangwen Liao is currently an associated professor at Fuzhou University, China. He received his PhD degree in computer architecture from Institute of Computer Sciences, Chinese Academy of Sciences, China in 2009. His research interests include natural language processing, information retrieval and extraction, and social media analysis.

Houdong Zheng received his Master degree in computer science from College of Mathematics and Computer Sciences, Fuzhou University, China in 2017. His research interests include natural language processing, information retrieval and extraction, and social media analysis.

Guolong Chen is currently a professor at Fuzhou University, China. He received his PhD degree in computer science from Xi’an Jiaotong University, China in 2002. His main research interests include computing intelligence, network science, big data processing, very large scale integration, etc.

Xueqi Cheng is a professor at Institute of Computing Technology (ICT), Chinese Academy of Sciences (CAS), China. He received his PhD degree in computer science from ICT, CAS in 2006. His current research interests include social computing, information retrieval, big data analysis, etc.

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Wei, J., Liao, X., Zheng, H. et al. Learning from context: A mutual reinforcement model for Chinese microblog opinion retrieval. Front. Comput. Sci. 12, 714–724 (2018). https://doi.org/10.1007/s11704-016-6163-5

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  • DOI: https://doi.org/10.1007/s11704-016-6163-5

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