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Research on the Best Time to Intervene into Network Public Opinion for Managers -Based on "Nankai Buick Affair"-

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Abstract

This study is based on network public opinion of the case - ”Nankai Buick Affair”. The daily number of posts as the variable, quantitative research is carried out on the law of change in network public opinion, which provides the scientific basis for managers to choose the best time to intervene. This article first begins from the three aspects: a number of changes in daily posts over time, the constitute of main topics and statistical analysis, and then gives a in-depth analysis of the law of change in network public opinion. After the emergency, performed by the number of posts, the shape of the rise and fall in network public opinion has three categories: sharp peak, severe right-skewed and fat tail. On this basis, then we study the changes of major issues in network public opinion in different stages: In the two periods: “Start- Peak” and “Peak-End”, not only the number of posts in BBS is not the same, but also the main topics in the BBS articles are different for the network public opinion of emergency. Finally, points out, If the managers issue truth of the incident in the prime time through the channels of authority, we can reduce the distance between the peak and the state of equilibrium for the network public opinion system, which is conducive to a smooth landing public opinion and social harmony.

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© 2009 ICST Institute for Computer Science, Social Informatics and Telecommunications Engineering

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Chen, M., Liu, Y. (2009). Research on the Best Time to Intervene into Network Public Opinion for Managers -Based on "Nankai Buick Affair"-. In: Zhou, J. (eds) Complex Sciences. Complex 2009. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 5. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02469-6_108

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  • DOI: https://doi.org/10.1007/978-3-642-02469-6_108

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-02468-9

  • Online ISBN: 978-3-642-02469-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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