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Analysing the Evolution of Contrary Opinions on a Controversial Network Event

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Neural Information Processing (ICONIP 2017)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10638))

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Abstract

With the growing popularity of social networking services, network public opinion gradually plays an important role in social life. When a controversial network event happens, what people concern about is which opinion in the contrary opinions will be widely accepted by people and how long this event lasts. To solve this problem, we propose a social evolutionary game model based on Hawk-Dove game to simulate how contrary opinions evolve in social network. The effectiveness of our model is validated by actual data. This model can be used to estimate the potential dominant opinion group and the time length of the controversy. Besides, our simulation reveals some special features of the evolution process and results. This study may be useful for network public opinion supervision and market research.

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Authors and Affiliations

  1. Institute of Computer Science, Tsinghua University, Haidian District, Beijing, China

    Qu Liu & Chuang Lin

  2. Institute of Computing Technology, Chinese Academy of Science, Haidian District, Beijing, China

    Yuanzhuo Wang & Guoliang Xing

Authors
  1. Qu Liu
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  2. Yuanzhuo Wang
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  3. Chuang Lin
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  4. Guoliang Xing
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Corresponding author

Correspondence to Chuang Lin .

Editor information

Editors and Affiliations

  1. Guangdong University of Technology, Guangzhou, China

    Derong Liu

  2. Guangdong University of Technology, Guangzhou, China

    Shengli Xie

  3. South China University of Technology, Guangzhou, China

    Yuanqing Li

  4. Institute of Automation, Chinese Academy of Sciences, Beijing, China

    Dongbin Zhao

  5. King Fahd University of Petroleum and Minerals, Dhahran, Saudi Arabia

    El-Sayed M. El-Alfy

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Liu, Q., Wang, Y., Lin, C., Xing, G. (2017). Analysing the Evolution of Contrary Opinions on a Controversial Network Event. In: Liu, D., Xie, S., Li, Y., Zhao, D., El-Alfy, ES. (eds) Neural Information Processing. ICONIP 2017. Lecture Notes in Computer Science(), vol 10638. Springer, Cham. https://doi.org/10.1007/978-3-319-70139-4_70

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  • DOI: https://doi.org/10.1007/978-3-319-70139-4_70

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-70138-7

  • Online ISBN: 978-3-319-70139-4

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