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Social balance in signed networks


  • Xiaolong Zheng

    () (Chinese Academy of Sciences
    Chinese Academy of Sciences
    University of Arizona)

  • Daniel Zeng

    (Chinese Academy of Sciences
    Chinese Academy of Sciences)

  • Fei-Yue Wang

    () (Chinese Academy of Sciences
    Chinese Academy of Sciences)


The theory of social balance, also called structural balance, is first proposed by Heider in 1940s, which is utilized to describe the potential social dynamics process. This theory is of great importance in sociology, computer science, psychology and other disciplines where social systems can be represented as signed networks. The social balance problem is hard but very interesting. It has attracted many researchers from various fields working on it over the past few years. Many significant theories and approaches have been developed and now exhibit tremendous potential for future applications. A comprehensive review of these existing studies can provide us significant insights into understanding the dynamic patterns of social systems. Yet to our investigation, existing studies have not done this, especially from a dynamical perspective. In this paper, we make an attempt towards conducting a brief survey of these scientific activities on social balance. Our efforts aim to review what has been done so far in this evolving area. We firstly introduce the fundamental concepts and significant properties of social balance. Then we summarize the existing balance measures and present detecting/partitioning algorithms, as well as important empirical investigations in both physical world and cyberspace. We next mainly focus on describing and comparing the fundamental mechanisms of the dynamics models. Several existing problems not yet satisfactorily solved in this area are also discussed.

Suggested Citation

  • Xiaolong Zheng & Daniel Zeng & Fei-Yue Wang, 2015. "Social balance in signed networks," Information Systems Frontiers, Springer, vol. 17(5), pages 1077-1095, October.
  • Handle: RePEc:spr:infosf:v:17:y:2015:i:5:d:10.1007_s10796-014-9483-8
    DOI: 10.1007/s10796-014-9483-8

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    Cited by:

    1. Maximilian Sadilek & Peter Klimek & Stefan Thurner, 2018. "Asocial balance—how your friends determine your enemies: understanding the co-evolution of friendship and enmity interactions in a virtual world," Journal of Computational Social Science, Springer, vol. 1(1), pages 227-239, January.
    2. Gaganmeet Kaur Awal & K. K. Bharadwaj, 2019. "Leveraging collective intelligence for behavioral prediction in signed social networks through evolutionary approach," Information Systems Frontiers, Springer, vol. 21(2), pages 417-439, April.


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