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Study on the Monitoring and Guidance of Public Opinion of Micro-Blog Based on Complex Network in Colleges and Universities

Received: 27 December 2017    Accepted:     Published: 28 December 2017
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Abstract

With the advent of the information age, the Internet has become the most important platform for people to express their opinions and attitudes toward public affairs or hot emergencies. Micro-blog public opinion has become the most influential network of public opinion of the means of transmission, with a short time, a wide range of communication features. Based on the analysis of complex network characteristics and network public opinion, this paper analyzes the complex network topological properties of complex network using the statistical properties of complex networks, the number of nodes, the point intensity and the average weighted clustering coefficient. Choosing "heat" and "situation" "And other indicators and node number, degree distribution and average weighted clustering coefficient of these three complex network parameters to achieve one-to-one mapping, and network life cycle of public opinion four-stage characteristics of building an emergency network public opinion monitoring and guidance model, public opinion real-time Monitoring, to determine the appropriate public opinion to guide the strategy. The actual public opinion monitoring and guidance through actual cases and real data verify the feasibility of the network public opinion monitoring and guidance model.

Published in Science Discovery (Volume 5, Issue 7)
DOI 10.11648/j.sd.20170507.16
Page(s) 509-514
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

University Micro-Blog Public Opinion, Complex Network, Monitoring and Guidance

References
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  • APA Style

    Gao Weimin, Chang Yunjie. (2017). Study on the Monitoring and Guidance of Public Opinion of Micro-Blog Based on Complex Network in Colleges and Universities. Science Discovery, 5(7), 509-514. https://doi.org/10.11648/j.sd.20170507.16

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    ACS Style

    Gao Weimin; Chang Yunjie. Study on the Monitoring and Guidance of Public Opinion of Micro-Blog Based on Complex Network in Colleges and Universities. Sci. Discov. 2017, 5(7), 509-514. doi: 10.11648/j.sd.20170507.16

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    AMA Style

    Gao Weimin, Chang Yunjie. Study on the Monitoring and Guidance of Public Opinion of Micro-Blog Based on Complex Network in Colleges and Universities. Sci Discov. 2017;5(7):509-514. doi: 10.11648/j.sd.20170507.16

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  • @article{10.11648/j.sd.20170507.16,
      author = {Gao Weimin and Chang Yunjie},
      title = {Study on the Monitoring and Guidance of Public Opinion of Micro-Blog Based on Complex Network in Colleges and Universities},
      journal = {Science Discovery},
      volume = {5},
      number = {7},
      pages = {509-514},
      doi = {10.11648/j.sd.20170507.16},
      url = {https://doi.org/10.11648/j.sd.20170507.16},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.sd.20170507.16},
      abstract = {With the advent of the information age, the Internet has become the most important platform for people to express their opinions and attitudes toward public affairs or hot emergencies. Micro-blog public opinion has become the most influential network of public opinion of the means of transmission, with a short time, a wide range of communication features. Based on the analysis of complex network characteristics and network public opinion, this paper analyzes the complex network topological properties of complex network using the statistical properties of complex networks, the number of nodes, the point intensity and the average weighted clustering coefficient. Choosing "heat" and "situation" "And other indicators and node number, degree distribution and average weighted clustering coefficient of these three complex network parameters to achieve one-to-one mapping, and network life cycle of public opinion four-stage characteristics of building an emergency network public opinion monitoring and guidance model, public opinion real-time Monitoring, to determine the appropriate public opinion to guide the strategy. The actual public opinion monitoring and guidance through actual cases and real data verify the feasibility of the network public opinion monitoring and guidance model.},
     year = {2017}
    }
    

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    T1  - Study on the Monitoring and Guidance of Public Opinion of Micro-Blog Based on Complex Network in Colleges and Universities
    AU  - Gao Weimin
    AU  - Chang Yunjie
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    JO  - Science Discovery
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    AB  - With the advent of the information age, the Internet has become the most important platform for people to express their opinions and attitudes toward public affairs or hot emergencies. Micro-blog public opinion has become the most influential network of public opinion of the means of transmission, with a short time, a wide range of communication features. Based on the analysis of complex network characteristics and network public opinion, this paper analyzes the complex network topological properties of complex network using the statistical properties of complex networks, the number of nodes, the point intensity and the average weighted clustering coefficient. Choosing "heat" and "situation" "And other indicators and node number, degree distribution and average weighted clustering coefficient of these three complex network parameters to achieve one-to-one mapping, and network life cycle of public opinion four-stage characteristics of building an emergency network public opinion monitoring and guidance model, public opinion real-time Monitoring, to determine the appropriate public opinion to guide the strategy. The actual public opinion monitoring and guidance through actual cases and real data verify the feasibility of the network public opinion monitoring and guidance model.
    VL  - 5
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    ER  - 

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Author Information
  • Computer and Information Science Department, Hunan Institute of Technology, Hengyang, China

  • Computer and Information Science Department, Hunan Institute of Technology, Hengyang, China

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