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Stabilizing social structure via modifying local patterns

Author

Listed:
  • Sajjad Salehi

    (University of Tehran)

  • Fattaneh Taghiyareh

    (University of Tehran)

Abstract

Study of social structure patterns and their dynamics has attracted more attentions in recent years. Structural measures like structural balance and status theory focus on patterns of signed links and the frequency/popularity of them. Several recent works have tried to define some measures to study the instability of social structure. But these works do not present any idea about the links that changing their signs makes the network more stable. In this paper, we have introduced three algorithms for detecting and changing the sign of links of graph to make it more stable. The results of simulation for a number of scale-free and complete networks show that proposed algorithms have the ability to create more stable patterns. As the proposed algorithms focus on components of the social network to calculate localized measures, it is appropriate for agent based models to study other social phenomena.

Suggested Citation

  • Sajjad Salehi & Fattaneh Taghiyareh, 2020. "Stabilizing social structure via modifying local patterns," Journal of Combinatorial Optimization, Springer, vol. 39(4), pages 1079-1095, May.
    • Handle: RePEc:spr:jcomop:v:39:y:2020:i:4:d:10.1007_s10878-020-00546-8
    DOI: 10.1007/s10878-020-00546-8
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    References listed on IDEAS

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    1. repec:cup:cbooks:9780511771576 is not listed on IDEAS
    2. Krzysztof Kułakowski & Przemysław Gawroński & Piotr Gronek, 2005. "The Heider Balance: A Continuous Approach," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 16(05), pages 707-716.
    3. Falk Hüffner & Nadja Betzler & Rolf Niedermeier, 2010. "Separator-based data reduction for signed graph balancing," Journal of Combinatorial Optimization, Springer, vol. 20(4), pages 335-360, November.
    4. Easley,David & Kleinberg,Jon, 2010. "Networks, Crowds, and Markets," Cambridge Books, Cambridge University Press, number 9780521195331.
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