IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v486y2017icp567-578.html
   My bibliography  Save this article

Topological evolution of the internet public opinion

Author

Listed:
  • Lian, Ying
  • Dong, Xuefan
  • Liu, Yijun

Abstract

The Internet forms a platform featured with high liquidity, accessibility and concealment for the public to express their respective views on certain events, thus leading to a large network graph. Due to such environmental features, the public opinions formed on the Internet are different from those on traditional media. Studies focusing on the former area are relatively fewer. In addition, the majority of existing methods proposed for constructing the Internet public opinion topological structure are based on the classic BA model, thus resulting in drawbacks in the range of simplicity and a lack of strict deduction. Therefore, based on the complex networks theory, a model applied to describe the topology of the Internet public opinion is deduced with rigorous derivation in the present paper. Results show that the proposed expression could well reflect the degree distribution of Internet public opinion which follows an analogous power law distribution, and that the peak value and the degree distribution are not correlative to each other. Moreover, it has been also proved that compared to the classic BA model, the proposed model has better accuracy performance in the description of the degree distribution of the Internet public opinion, which contributes to future studies focusing on this area. Thus, an attempt has been made to give the first theoretical description of the Internet public opinion topology in the present paper. In addition, it is also the first paper focusing on the solution of networks degree distribution with an exponential growth form.

Suggested Citation

  • Lian, Ying & Dong, Xuefan & Liu, Yijun, 2017. "Topological evolution of the internet public opinion," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 486(C), pages 567-578.
  • Handle: RePEc:eee:phsmap:v:486:y:2017:i:c:p:567-578
    DOI: 10.1016/j.physa.2017.05.034
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437117305526
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000

    File URL: https://libkey.io/10.1016/j.physa.2017.05.034?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Barabási, Albert-László & Albert, Réka & Jeong, Hawoong, 2000. "Scale-free characteristics of random networks: the topology of the world-wide web," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 281(1), pages 69-77.
    2. Sara Binzer Hobolt & Robert Klemmemsen, 2005. "Responsive Government? Public Opinion and Government Policy Preferences in Britain and Denmark," Political Studies, Political Studies Association, vol. 53(2), pages 379-402, June.
    3. Jie Yan & Dimitris Assimakopoulos, 2009. "The small-world and scale-free structure of an internet technological community," International Journal of Information Technology and Management, Inderscience Enterprises Ltd, vol. 8(1), pages 33-49.
    4. Hunter, David R. & Goodreau, Steven M. & Handcock, Mark S., 2008. "Goodness of Fit of Social Network Models," Journal of the American Statistical Association, American Statistical Association, vol. 103, pages 248-258, March.
    5. Barabási, Albert-László & Albert, Réka & Jeong, Hawoong, 1999. "Mean-field theory for scale-free random networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 272(1), pages 173-187.
    6. Yue Wu & Yong Hu & Xiao-Hai He, 2013. "Public Opinion Formation Model Based On Opinion Entropy," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 24(11), pages 1-13.
    7. Sara Binzer Hobolt & Robert Klemmemsen, 2005. "Responsive Government? Public Opinion and Government Policy Preferences in Britain and Denmark," Political Studies, Political Studies Association, vol. 53, pages 379-402, June.
    8. Xingang Wang, 2010. "Pattern evolution in non-synchronizable scale-free networks," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 75(3), pages 285-297, June.
    9. Steven H. Strogatz, 2001. "Exploring complex networks," Nature, Nature, vol. 410(6825), pages 268-276, March.
    10. Shuguang Suo & Yu Chen, 2008. "The Dynamics of Public Opinion in Complex Networks," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 11(4), pages 1-2.
    11. Jie Yan & Dimitris Assimakopoulos, 2008. "The small-world and scale-free structure of an internet technological community," Post-Print hal-02313383, HAL.
    12. Duncan J. Watts & Peter Sheridan Dodds, 2007. "Influentials, Networks, and Public Opinion Formation," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 34(4), pages 441-458, May.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Ying Lian & Xiaofeng Lin & Xuefan Dong & Shengjie Hou, 2022. "A Normalized Rich-Club Connectivity-Based Strategy for Keyword Selection in Social Media Analysis," Sustainability, MDPI, vol. 14(13), pages 1-19, June.
    2. Lian, Ying & Liu, Yijun & Dong, Xuefan, 2020. "Strategies for controlling false online information during natural disasters: The case of Typhoon Mangkhut in China," Technology in Society, Elsevier, vol. 62(C).
    3. Hakim Akeb & Aldo Lévy & Mohamed Rdali, 2022. "A quantitative method for opinion ratings and analysis: an event study," Annals of Operations Research, Springer, vol. 313(2), pages 625-638, June.
    4. Yanlan Mei & Yan Tu & Kefan Xie & Yicheng Ye & Wenjing Shen, 2019. "Internet Public Opinion Risk Grading under Emergency Event Based on AHPSort II-DEMATEL," Sustainability, MDPI, vol. 11(16), pages 1-16, August.
    5. Dong, Xuefan & Lian, Ying, 2021. "A review of social media-based public opinion analyses: Challenges and recommendations," Technology in Society, Elsevier, vol. 67(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Dong, Xuefan & Liu, Yijung & Wu, Chao & Lian, Ying, 2019. "The topology of scale-free networks with an S-shaped nonlinear growth characteristic," Chaos, Solitons & Fractals, Elsevier, vol. 121(C), pages 137-148.
    2. Chen, Qinghua & Shi, Dinghua, 2006. "Markov chains theory for scale-free networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 360(1), pages 121-133.
    3. Yao, Xin & Zhang, Chang-shui & Chen, Jin-wen & Li, Yan-da, 2005. "On the formation of degree and cluster-degree correlations in scale-free networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 353(C), pages 661-673.
    4. Ruiz Vargas, E. & Mitchell, D.G.V. & Greening, S.G. & Wahl, L.M., 2014. "Topology of whole-brain functional MRI networks: Improving the truncated scale-free model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 405(C), pages 151-158.
    5. Xiao Tang & Weiwei Chen & Tian Wu, 2018. "Do Authoritarian Governments Respond to Public Opinion on the Environment? Evidence from China," IJERPH, MDPI, vol. 15(2), pages 1-15, February.
    6. Rong, Rong & Houser, Daniel, 2015. "Growing stars: A laboratory analysis of network formation," Journal of Economic Behavior & Organization, Elsevier, vol. 117(C), pages 380-394.
    7. Li, Chunguang & Chen, Guanrong, 2004. "Synchronization in general complex dynamical networks with coupling delays," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 343(C), pages 263-278.
    8. Laurienti, Paul J. & Joyce, Karen E. & Telesford, Qawi K. & Burdette, Jonathan H. & Hayasaka, Satoru, 2011. "Universal fractal scaling of self-organized networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(20), pages 3608-3613.
    9. L. Jarina Banu & P. Balasubramaniam, 2014. "Synchronisation of discrete-time complex networks with randomly occurring uncertainties, nonlinearities and time-delays," International Journal of Systems Science, Taylor & Francis Journals, vol. 45(7), pages 1427-1450, July.
    10. Chen, Qinghua & Shi, Dinghua, 2004. "The modeling of scale-free networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 335(1), pages 240-248.
    11. Wang, Huan & Xu, Chuan-Yun & Hu, Jing-Bo & Cao, Ke-Fei, 2014. "A complex network analysis of hypertension-related genes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 394(C), pages 166-176.
    12. Hema Yoganarasimhan, 2012. "Impact of social network structure on content propagation: A study using YouTube data," Quantitative Marketing and Economics (QME), Springer, vol. 10(1), pages 111-150, March.
    13. Jackman, Mahalia, 2019. "Religion, contact and ambivalent attitudes towards the rights of gays and lesbians in Barbados," SocArXiv 528bt, Center for Open Science.
    14. Li, Jianyu & Zhou, Jie, 2007. "Chinese character structure analysis based on complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 380(C), pages 629-638.
    15. Liu, Z.X. & Chen, Z.Q. & Yuan, Z.Z., 2007. "Pinning control of weighted general complex dynamical networks with time delay," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 375(1), pages 345-354.
    16. Wang, Yanhui & Bi, Lifeng & Lin, Shuai & Li, Man & Shi, Hao, 2017. "A complex network-based importance measure for mechatronics systems," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 466(C), pages 180-198.
    17. Wen, Guanghui & Duan, Zhisheng & Chen, Guanrong & Geng, Xianmin, 2011. "A weighted local-world evolving network model with aging nodes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(21), pages 4012-4026.
    18. Daniel Straulino & Mattie Landman & Neave O'Clery, 2020. "A bi-directional approach to comparing the modular structure of networks," Papers 2010.06568, arXiv.org.
    19. Dhal, R. & Abad Torres, J. & Roy, S., 2015. "Detecting link failures in complex network processes using remote monitoring," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 437(C), pages 36-54.
    20. Santiago, A. & Benito, R.M., 2008. "Connectivity degrees in the threshold preferential attachment model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(10), pages 2365-2376.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:phsmap:v:486:y:2017:i:c:p:567-578. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.