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Self-organization and social science

Author

Listed:
  • David Anzola

    (University of Surrey)

  • Peter Barbrook-Johnson

    (University of Surrey)

  • Juan I. Cano

    (University of Surrey)

Abstract

Complexity science and its methodological applications have increased in popularity in social science during the last two decades. One key concept within complexity science is that of self-organization. Self-organization is used to refer to the emergence of stable patterns through autonomous and self-reinforcing dynamics at the micro-level. In spite of its potential relevance for the study of social dynamics, the articulation and use of the concept of self-organization has been kept within the boundaries of complexity science and links to and from mainstream social science are scarce. These links can be difficult to establish, even for researchers working in social complexity with a background in social science, because of the theoretical and conceptual diversity and fragmentation in traditional social science. This article is meant to serve as a first step in the process of overcoming this lack of cross-fertilization between complexity and mainstream social science. A systematic review of the concept of self-organization and a critical discussion of similar notions in mainstream social science is presented, in an effort to help practitioners within subareas of complexity science to identify literature from traditional social science that could potentially inform their research.

Suggested Citation

  • David Anzola & Peter Barbrook-Johnson & Juan I. Cano, 2017. "Self-organization and social science," Computational and Mathematical Organization Theory, Springer, vol. 23(2), pages 221-257, June.
  • Handle: RePEc:spr:comaot:v:23:y:2017:i:2:d:10.1007_s10588-016-9224-2
    DOI: 10.1007/s10588-016-9224-2
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    4. de Moura, Fernanda Senra & Barbrook-Johnson, Peter, 2022. "Using data-driven systems mapping to contextualise complexity economics insights," INET Oxford Working Papers 2022-27, Institute for New Economic Thinking at the Oxford Martin School, University of Oxford.
    5. Munjal, Puja & Kumar, Lalit & Kumar, Sandeep & Banati, Hema, 2019. "Evidence of Ostwald Ripening in opinion driven dynamics of mutually competitive social networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 522(C), pages 182-194.
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