IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v507y2018icp427-434.html
   My bibliography  Save this article

Evolutionary of online social networks driven by pareto wealth distribution and bidirectional preferential attachment

Author

Listed:
  • Zhou, Bin
  • Yan, Xiao-Yong
  • Xu, Xiao-Ke
  • Xu, Xiao-Ting
  • Wang, Nianxin

Abstract

Understanding of the evolutionary mechanism of online social networks is greatly significant for the development of network science, but up to now most present researches on this topic have not enough insight. In this study, firstly we empirically showed the essential evolution characteristics of Renren online social network. The evolution mechanism of online social networks is explained by the perspective of Pareto wealth distribution and bidirectional preferential attachment. Then a novel model is proposed to reproduce the evolution characteristics which are consistent with the ones of Renren online social network, and the evolutionary analytical solution to the proposed model was presented. The results suggest that both Pareto wealth distribution and bidirectional preferential attachment play an important role in the evolution process of online social networks and can help us to understand the evolutionary origin of online social networks. The model has significant implications for dynamic simulation researches of social networks, especially in information diffusion through online communities and infection spreading in real societies.

Suggested Citation

  • Zhou, Bin & Yan, Xiao-Yong & Xu, Xiao-Ke & Xu, Xiao-Ting & Wang, Nianxin, 2018. "Evolutionary of online social networks driven by pareto wealth distribution and bidirectional preferential attachment," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 507(C), pages 427-434.
    • Handle: RePEc:eee:phsmap:v:507:y:2018:i:c:p:427-434
    DOI: 10.1016/j.physa.2018.05.049
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437118305934
    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.2018.05.049?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. Levy, Moshe & Solomon, Sorin, 1997. "New evidence for the power-law distribution of wealth," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 242(1), pages 90-94.
    2. Samer Faraj & Sirkka L. Jarvenpaa & Ann Majchrzak, 2011. "Knowledge Collaboration in Online Communities," Organization Science, INFORMS, vol. 22(5), pages 1224-1239, October.
    3. Klass, Oren S. & Biham, Ofer & Levy, Moshe & Malcai, Ofer & Solomon, Sorin, 2006. "The Forbes 400 and the Pareto wealth distribution," Economics Letters, Elsevier, vol. 90(2), pages 290-295, February.
    4. Lambiotte, R. & Panzarasa, P., 2009. "Communities, knowledge creation, and information diffusion," Journal of Informetrics, Elsevier, vol. 3(3), pages 180-190.
    5. Marcel Salathé & James H Jones, 2010. "Dynamics and Control of Diseases in Networks with Community Structure," PLOS Computational Biology, Public Library of Science, vol. 6(4), pages 1-11, April.
    6. Toivonen, Riitta & Onnela, Jukka-Pekka & Saramäki, Jari & Hyvönen, Jörkki & Kaski, Kimmo, 2006. "A model for social networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 371(2), pages 851-860.
    7. M. E. J. Newman & Aaron Clauset, 2016. "Structure and inference in annotated networks," Nature Communications, Nature, vol. 7(1), pages 1-11, September.
    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. Wang, Zhiping & Yin, Haofei & Jiang, Xin, 2020. "Exploring the dynamic growth mechanism of social networks using evolutionary hypergraph," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 544(C).
    2. Zhou, Bin & Xu, Xiao-Ting & Liu, Jian-Guo & Xu, Xiao-Ke & Wang, Nianxin, 2019. "Information interaction model for the mobile communication networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 1170-1176.

    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. Zhou, Bin & Xu, Xiao-Ting & Liu, Jian-Guo & Xu, Xiao-Ke & Wang, Nianxin, 2019. "Information interaction model for the mobile communication networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 1170-1176.
    2. Philip Vermeulen, 2018. "How Fat is the Top Tail of the Wealth Distribution?," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 64(2), pages 357-387, June.
    3. Becker, Bo & Cronqvist, Henrik & Fahlenbrach, Rüdiger, 2011. "Estimating the Effects of Large Shareholders Using a Geographic Instrument," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 46(4), pages 907-942, August.
    4. Arun Advani & George Bangham & Jack Leslie, 2021. "The UK's wealth distribution and characteristics of high‐wealth households," Fiscal Studies, John Wiley & Sons, vol. 42(3-4), pages 397-430, September.
    5. Hric, Darko & Kaski, Kimmo & Kivelä, Mikko, 2018. "Stochastic block model reveals maps of citation patterns and their evolution in time," Journal of Informetrics, Elsevier, vol. 12(3), pages 757-783.
    6. Jayadev, Arjun, 2008. "A power law tail in India's wealth distribution: Evidence from survey data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(1), pages 270-276.
    7. Frank A. Cowell & Philippe Kerm, 2015. "Wealth Inequality: A Survey," Journal of Economic Surveys, Wiley Blackwell, vol. 29(4), pages 671-710, September.
    8. Wang, Yuanjun & You, Shibing, 2016. "An alternative method for modeling the size distribution of top wealth," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 457(C), pages 443-453.
    9. Tomson Ogwang, 2011. "Power laws in top wealth distributions: evidence from Canada," Empirical Economics, Springer, vol. 41(2), pages 473-486, October.
    10. Ogwang, Tomson, 2013. "Is the wealth of the world’s billionaires Paretian?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(4), pages 757-762.
    11. Jess Benhabib & Shenghao Zhu, 2008. "Age, Luck, and Inheritance," NBER Working Papers 14128, National Bureau of Economic Research, Inc.
    12. Jos'e Cl'audio do Nascimento, 2019. "Rational hyperbolic discounting," Papers 1910.05209, arXiv.org, revised Feb 2020.
    13. Aloys Prinz, 2016. "Do capitalistic institutions breed billionaires?," Empirical Economics, Springer, vol. 51(4), pages 1319-1332, December.
    14. Michal Brzezinski & Katarzyna Sałach & Marcin Wroński, 2019. "Wealth inequality in Central and Eastern Europe: evidence from joined household survey and rich lists’ data," Working Papers 2019-09, Faculty of Economic Sciences, University of Warsaw.
    15. do Nascimento, José Cláudio, 2021. "The personal wealth importance to the intertemporal choice," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 565(C).
    16. Hongduo Cao & Ying Li & Yong Tan, 2014. "The synchronization club: classification of global economic groups by inequality," Applied Economics, Taylor & Francis Journals, vol. 46(21), pages 2502-2510, July.
    17. Zhao, Narisa & Cui, Xuelian, 2017. "Impact of individual interest shift on information dissemination in modular networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 466(C), pages 232-242.
    18. Jos'e Cl'audio do Nascimento, 2019. "Decision-making and Fuzzy Temporal Logic," Papers 1901.01970, arXiv.org, revised Feb 2019.
    19. Capehart, Kevin W., 2014. "Is the wealth of the world’s billionaires not Paretian?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 395(C), pages 255-260.
    20. Daniel Torres-Salinas & Nicolás Robinson-García & Álvaro Cabezas-Clavijo & Evaristo Jiménez-Contreras, 2014. "Analyzing the citation characteristics of books: edited books, book series and publisher types in the book citation index," Scientometrics, Springer;Akadémiai Kiadó, vol. 98(3), pages 2113-2127, March.

    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:507:y:2018:i:c:p:427-434. 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.