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Keyword-Based Semantic Analysis of Microblog for Public Opinion Study in Online Collective Behaviors

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Web-Age Information Management (WAIM 2014)

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Abstract

This study employs text mining and semantic analysis methods to analyze the change of public opinion in the formation of online collective behaviors in crisis management. A case that related to law enforcement violence is investigated to study the communication between government and the public. The development of event is framed based on news data. The paper conducts a semantic analysis on microblog data and extracts high-frequency keywords and co-occurrence words at each stage of the event. By comparing key words at different stages, the paper proposes a new way to gain insight into the requirement of the public and predict the change of public opinion.

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Acknowledgement

This work was partially supported by the National Natural Science Foundation of China (Grant No.91024032, No.91224008, No.70833003). National Basic Research Program of China (973 Program No: 2012CB719705).

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Correspondence to Hui Zhang .

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Ma, Y., Deng, Q., Wang, X., Liu, J., Zhang, H. (2014). Keyword-Based Semantic Analysis of Microblog for Public Opinion Study in Online Collective Behaviors. In: Chen, Y., et al. Web-Age Information Management. WAIM 2014. Lecture Notes in Computer Science(), vol 8597. Springer, Cham. https://doi.org/10.1007/978-3-319-11538-2_5

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  • DOI: https://doi.org/10.1007/978-3-319-11538-2_5

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-11537-5

  • Online ISBN: 978-3-319-11538-2

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