IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v573y2021ics037843712100248x.html
   My bibliography  Save this article

Quantifying the social structure of elites in ancient China

Author

Listed:
  • Jiang, Xiongfei
  • Xiong, Long
  • Bai, Ling
  • Zhao, Na
  • Zhang, Jiu
  • Xia, Ke
  • Deng, Kai
  • Zheng, Bo

Abstract

With data from epitaphs of elites in ancient China, we construct the elite social networks of the Tang-dynasty and the Song-dynasty. The complexity theory is then introduced to unveil associations between the elite social networks and the history. The top influential elites in ancient China are identified from the elite social networks. We detect the community structure formed with strongly connected elites, and investigate the interactions between the communities. It is observed that the elite social networks of the Tang-dynasty and the Song-dynasty exhibit the neutral and disassortative mixing patterns, respectively. Additionally, this work quantitatively supports the Tang-Song Transition Hypothesis.

Suggested Citation

  • Jiang, Xiongfei & Xiong, Long & Bai, Ling & Zhao, Na & Zhang, Jiu & Xia, Ke & Deng, Kai & Zheng, Bo, 2021. "Quantifying the social structure of elites in ancient China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 573(C).
    • Handle: RePEc:eee:phsmap:v:573:y:2021:i:c:s037843712100248x
    DOI: 10.1016/j.physa.2021.125976
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S037843712100248X
    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.2021.125976?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. Thomas T. Hills & Eugenio Proto & Daniel Sgroi & Chanuki Illushka Seresinhe, 2019. "Historical analysis of national subjective wellbeing using millions of digitized books," Nature Human Behaviour, Nature, vol. 3(12), pages 1271-1275, December.
    2. X. F. Jiang & B. Zheng, 2012. "Anti-correlation and subsector structure in financial systems," Papers 1201.6418, arXiv.org.
    3. Edward L. Huttlin & Raphael J. Bruckner & Joao A. Paulo & Joe R. Cannon & Lily Ting & Kurt Baltier & Greg Colby & Fana Gebreab & Melanie P. Gygi & Hannah Parzen & John Szpyt & Stanley Tam & Gabriela Z, 2017. "Architecture of the human interactome defines protein communities and disease networks," Nature, Nature, vol. 545(7655), pages 505-509, May.
    4. X. F. Jiang & T. T. Chen & B. Zheng, 2014. "Structure of local interactions in complex financial dynamics," Papers 1406.0070, arXiv.org.
    5. Li, Yan & Jiang, Xiong-Fei & Tian, Yue & Li, Sai-Ping & Zheng, Bo, 2019. "Portfolio optimization based on network topology," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 515(C), pages 671-681.
    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. Bai, Ling & Xiong, Long & Zhao, Na & Xia, Ke & Jiang, Xiong-Fei, 2022. "Dynamical structure of social map in ancient China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 607(C).
    2. Jiang, Xiong-Fei & Xiong, Long & Bai, Ling & Lin, Jie & Zhang, Jing-Feng & Yan, Kun & Zhu, Jia-Zhen & Zheng, Bo & Zheng, Jian-Jun, 2022. "Structure and dynamics of human complication-disease network," Chaos, Solitons & Fractals, Elsevier, vol. 164(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. Bai, Ling & Xiong, Long & Zhao, Na & Xia, Ke & Jiang, Xiong-Fei, 2022. "Dynamical structure of social map in ancient China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 607(C).
    2. Duc Thi Luu, 2022. "Portfolio Correlations in the Bank-Firm Credit Market of Japan," Computational Economics, Springer;Society for Computational Economics, vol. 60(2), pages 529-569, August.
    3. Zhang, Jiu & Jin, Li-Fu & Zheng, Bo & Li, Yan & Jiang, Xiong-Fei, 2022. "Simplified calculations of time correlation functions in non-stationary complex financial systems," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 589(C).
    4. T. T. Chen & B. Zheng & Y. Li & X. F. Jiang, 2017. "New approaches in agent-based modeling of complex financial systems," Papers 1703.06840, arXiv.org.
    5. Lei Tan & Bo Zheng & Jun-Jie Chen & Xiong-Fei Jiang, 2015. "How Volatilities Nonlocal in Time Affect the Price Dynamics in Complex Financial Systems," PLOS ONE, Public Library of Science, vol. 10(2), pages 1-16, February.
    6. Yan Li & Bo Zheng & Ting-Ting Chen & Xiong-Fei Jiang, 2017. "Fluctuation-driven price dynamics and investment strategies," PLOS ONE, Public Library of Science, vol. 12(12), pages 1-15, December.
    7. Gautier Marti & Frank Nielsen & Miko{l}aj Bi'nkowski & Philippe Donnat, 2017. "A review of two decades of correlations, hierarchies, networks and clustering in financial markets," Papers 1703.00485, arXiv.org, revised Nov 2020.
    8. Jiang, Xiong-Fei & Zheng, Bo & Ren, Fei & Qiu, Tian, 2017. "Localized motion in random matrix decomposition of complex financial systems," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 471(C), pages 154-161.
    9. Jun-Jie Chen & Lei Tan & Bo Zheng, 2015. "Agent-based model with multi-level herding for complex financial systems," Papers 1504.01811, arXiv.org.
    10. Chen, Huan & Mai, Yong & Li, Sai-Ping, 2014. "Analysis of network clustering behavior of the Chinese stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 414(C), pages 360-367.
    11. Yang, Ming-Yuan & Li, Sai-Ping & Wu, Yue & Tang, Jingtai & Ren, Fei, 2019. "Do government rescue policies reduce the market volatility after crash? Evidence from the Shanghai stock market," Finance Research Letters, Elsevier, vol. 29(C), pages 117-124.
    12. Chen, Ting-Ting & Zheng, Bo & Li, Yan & Jiang, Xiong-Fei, 2018. "Information driving force and its application in agent-based modeling," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 496(C), pages 593-601.
    13. Wang, Yan & Wang, Yue & Li, Ming-Xia, 2019. "Regional characteristics of sports industry profitability: Evidence from China’s province level data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 946-955.
    14. Lei Tan & Jun-Jie Chen & Bo Zheng & Fang-Yan Ouyang, 2016. "Exploring Market State and Stock Interactions on the Minute Timescale," PLOS ONE, Public Library of Science, vol. 11(2), pages 1-13, February.
    15. Brodeur, Abel & Clark, Andrew E. & Fleche, Sarah & Powdthavee, Nattavudh, 2021. "COVID-19, lockdowns and well-being: Evidence from Google Trends," Journal of Public Economics, Elsevier, vol. 193(C).
    16. Christophe Chorro & Emmanuelle Jay & Philippe De Peretti & Thibault Soler, 2021. "Frequency causality measures and Vector AutoRegressive (VAR) models: An improved subset selection method suited to parsimonious systems," Documents de travail du Centre d'Economie de la Sorbonne 21013, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
    17. Ouyang, F.Y. & Zheng, B. & Jiang, X.F., 2014. "Spatial and temporal structures of four financial markets in Greater China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 402(C), pages 236-244.
    18. Ali Kabiri & Harold James & John Landon‐Lane & David Tuckett & Rickard Nyman, 2023. "The role of sentiment in the US economy: 1920 to 1934," Economic History Review, Economic History Society, vol. 76(1), pages 3-30, February.
    19. Si, Jingjian & Zhou, Jinsheng & Gao, Xiangyun & Ze, Wang & Tao, Wu & Zhao, Yiran, 2022. "Reconstructing a complex financial network using compressed sensing based on low-frequency time series data," Finance Research Letters, Elsevier, vol. 49(C).
    20. Mattia Guerini & Duc Thi Luu & Mauro Napoletano, 2023. "Synchronization patterns in the European Union," Applied Economics, Taylor & Francis Journals, vol. 55(18), pages 2038-2059, April.

    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:573:y:2021:i:c:s037843712100248x. 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.