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Opinion data mining based on DNA method and ORA software

Author

Listed:
  • Tian, Ru-Ya
  • Wu, Lei
  • Liang, Xiao-He
  • Zhang, Xue-Fu

Abstract

Public opinion, especially the online public opinion is a critical issue when it comes to mining its characteristics. Because it can be formed directly and intensely in a short time, and may lead to the outbreak of online group events, and the formation of online public opinion crisis. This may become the pushing hand of a public crisis event, or even have negative social impacts, which brings great challenges to the government management. Data from the mass media which reveal implicit, previously unknown, and potentially valuable information, can effectively help us to understand the evolution law of public opinion, and provide a useful reference for rumor intervention. Based on the Dynamic Network Analysis method, this paper uses ORA software to mine characteristics of public opinion information, opinion topics, and public opinion agents through a series of indicators, and quantitatively analyzed the relationships between them. The results show that through the analysis of the 8 indexes associating with opinion data mining, we can have a basic understanding of the public opinion characteristics of an opinion event, such as who is important in the opinion spreading process, the information grasping condition, and the opinion topics release situation.

Suggested Citation

  • Tian, Ru-Ya & Wu, Lei & Liang, Xiao-He & Zhang, Xue-Fu, 2018. "Opinion data mining based on DNA method and ORA software," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 490(C), pages 1471-1480.
    • Handle: RePEc:eee:phsmap:v:490:y:2018:i:c:p:1471-1480
    DOI: 10.1016/j.physa.2017.08.093
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    References listed on IDEAS

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    1. Fortunato, Santo, 2005. "Damage spreading and opinion dynamics on scale-free networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 348(C), pages 683-690.
    2. Tian, Ru-Ya & Zhang, Xue-Fu & Liu, Yi-Jun, 2015. "SSIC model: A multi-layer model for intervention of online rumors spreading," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 427(C), pages 181-191.
    3. Orman, Günce Keziban & Labatut, Vincent & Naskali, Ahmet Teoman, 2017. "Exploring the evolution of node neighborhoods in Dynamic Networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 482(C), pages 375-391.
    4. F. A. Rodrigues & L. Da F. Costa, 2005. "Surviving Opinions In Sznajd Models On Complex Networks," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 16(11), pages 1785-1792.
    5. Stone, Thomas E. & McKay, Susan R., 2015. "Majority-vote model on a dynamic small-world network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 419(C), pages 437-443.
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    Cited by:

    1. Zhu, Hou & Hu, Bin, 2018. "Impact of information on public opinion reversal—An agent based model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 512(C), pages 578-587.

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