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Assessing the relevance of individual characteristics for the structure of similarity networks in new social strata in Shanghai

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  • Wang, Luo-Qing
  • Xu, Yong-Xiang

Abstract

Node characteristics are found to be a key ingredient to shape the link formation in complex networks. In this paper, we perform a detailed investigation on the influence of different node characteristics on the structure of similarity networks, which are constructed based on a unique data set of questionnaires. The basic personal information (including the gender, experience of studying abroad, religion, and registered permanent residence in Shanghai (Shanghai Hukou)) and social positions (including intention of solving social problems, economic wealth, social reputation, and political status) provided in the questionnaires are considered as node characteristics. The similarity networks are built according to the Euclidean distances calculated based on the answer vectors to the questions on personal traits. According to the indicator Θ based on entropy measures, in 87% of tests, the links within the nodes having the same characteristics and between the nodes possessing different characteristics are not randomly connected. We further find that the node characteristics have significant effects on the preference of node in forming links within similarity networks. Our work sheds a new light on understanding the relevance of node characteristics for network structures.

Suggested Citation

  • Wang, Luo-Qing & Xu, Yong-Xiang, 2018. "Assessing the relevance of individual characteristics for the structure of similarity networks in new social strata in Shanghai," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 509(C), pages 881-889.
    • Handle: RePEc:eee:phsmap:v:509:y:2018:i:c:p:881-889
    DOI: 10.1016/j.physa.2018.06.086
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    1. Gang-Jin Wang & Chi Xie & Shou Chen, 2017. "Multiscale correlation networks analysis of the US stock market: a wavelet analysis," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 12(3), pages 561-594, October.
    2. Wen-Jie Xie & Zhi-Qiang Jiang & Gao-Feng Gu & Xiong Xiong & Wei-Xing Zhou, 2015. "Joint multifractal analysis based on the partition function approach: Analytical analysis, numerical simulation and empirical application," Papers 1509.05952, arXiv.org.
    3. Wang, Gang-Jin & Jiang, Zhi-Qiang & Lin, Min & Xie, Chi & Stanley, H. Eugene, 2018. "Interconnectedness and systemic risk of China's financial institutions," Emerging Markets Review, Elsevier, vol. 35(C), pages 1-18.
    4. Ladislav Kristoufek, 2016. "Fractal approach towards power-law coherency to measure cross-correlations between time series," Papers 1608.06781, arXiv.org, revised Feb 2017.
    5. Jiang, Zhi-Qiang & Zhou, Wei-Xing, 2010. "Complex stock trading network among investors," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(21), pages 4929-4941.
    6. Fragkiskos Papadopoulos & Maksim Kitsak & M. Ángeles Serrano & Marián Boguñá & Dmitri Krioukov, 2012. "Popularity versus similarity in growing networks," Nature, Nature, vol. 489(7417), pages 537-540, September.
    7. Coren L. Apicella & Frank W. Marlowe & James H. Fowler & Nicholas A. Christakis, 2012. "Social networks and cooperation in hunter-gatherers," Nature, Nature, vol. 481(7382), pages 497-501, January.
    8. Jan Bentzen, 2007. "Does OPEC influence crude oil prices? Testing for co-movements and causality between regional crude oil prices," Applied Economics, Taylor & Francis Journals, vol. 39(11), pages 1375-1385.
    9. Výrost, Tomáš & Lyócsa, Štefan & Baumöhl, Eduard, 2015. "Granger causality stock market networks: Temporal proximity and preferential attachment," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 427(C), pages 262-276.
    10. Gang-Jin Wang & Chi Xie & Kaijian He & H. Eugene Stanley, 2017. "Extreme risk spillover network: application to financial institutions," Quantitative Finance, Taylor & Francis Journals, vol. 17(9), pages 1417-1433, September.
    11. Zhang, Yue-Jun & Wei, Yi-Ming, 2010. "The crude oil market and the gold market: Evidence for cointegration, causality and price discovery," Resources Policy, Elsevier, vol. 35(3), pages 168-177, September.
    12. Kristoufek, Ladislav, 2014. "Detrending moving-average cross-correlation coefficient: Measuring cross-correlations between non-stationary series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 406(C), pages 169-175.
    13. Xi-Yuan Qian & Ya-Min Liu & Zhi-Qiang Jiang & Boris Podobnik & Wei-Xing Zhou & H. Eugene Stanley, 2015. "Detrended partial cross-correlation analysis of two nonstationary time series influenced by common external forces," Papers 1504.02435, arXiv.org, revised Apr 2015.
    14. Gang-Jin Wang & Chi Xie & H. Eugene Stanley, 2018. "Correlation Structure and Evolution of World Stock Markets: Evidence from Pearson and Partial Correlation-Based Networks," Computational Economics, Springer;Society for Computational Economics, vol. 51(3), pages 607-635, March.
    15. Zhi-Qiang Jiang & Yan-Hong Yang & Gang-Jin Wang & Wei-Xing Zhou, 2016. "Joint multifractal analysis based on wavelet leaders," Papers 1611.00897, arXiv.org.
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