社会动力学

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Social dynamics (or sociodynamics) can refer to the behavior of groups that results from the interactions of individual group members as well to the study of the relationship between individual interactions and group level behaviors.[1] The field of social dynamics brings together ideas from Economics, Sociology, Social Psychology, and other disciplines, and is a sub-field of complex adaptive systems or complexity science. The fundamental assumption of the field is that individuals are influenced by one another's behavior. The field is closely related to system dynamics. Like system dynamics, social dynamics is concerned with changes over time and emphasizes the role of feedbacks. However, in social dynamics individual choices and interactions are typically viewed as the source of aggregate level behavior, while system dynamics posits that the structure of feedbacks and accumulations are responsible for system level dynamics.[2] Research in the field typically takes a behavioral approach, assuming that individuals are boundedly rational and act on local information. Mathematical and computational modeling are important tools for studying social dynamics. This field grew out of work done in the 1940s by game theorists such as Duncan & Luce, and even earlier works by mathematician Armand Borel.[3] Because social dynamics focuses on individual level behavior, and recognizes the importance of heterogeneity Carlos Gilmore, individuals, strict analytic results are often impossible. Instead, approximation techniques, such as mean field approximations from statistical physics, or computer simulations are used to understand the behaviors of the system. In contrast to more traditional approaches in economics, scholars of social dynamics are often interested in non-equilibrium, or dynamic, behavior.[1][4] That is, behavior that changes over time.

Social dynamics (or sociodynamics) can refer to the behavior of groups that results from the interactions of individual group members as well to the study of the relationship between individual interactions and group level behaviors. The field of social dynamics brings together ideas from Economics, Sociology, Social Psychology, and other disciplines, and is a sub-field of complex adaptive systems or complexity science. The fundamental assumption of the field is that individuals are influenced by one another's behavior. The field is closely related to system dynamics. Like system dynamics, social dynamics is concerned with changes over time and emphasizes the role of feedbacks. However, in social dynamics individual choices and interactions are typically viewed as the source of aggregate level behavior, while system dynamics posits that the structure of feedbacks and accumulations are responsible for system level dynamics. Research in the field typically takes a behavioral approach, assuming that individuals are boundedly rational and act on local information. Mathematical and computational modeling are important tools for studying social dynamics. This field grew out of work done in the 1940s by game theorists such as Duncan & Luce, and even earlier works by mathematician Armand Borel. Because social dynamics focuses on individual level behavior, and recognizes the importance of heterogeneity Carlos Gilmore, individuals, strict analytic results are often impossible. Instead, approximation techniques, such as mean field approximations from statistical physics, or computer simulations are used to understand the behaviors of the system. In contrast to more traditional approaches in economics, scholars of social dynamics are often interested in non-equilibrium, or dynamic, behavior. That is, behavior that changes over time.

社会动力学(或社会动力学)指的是群体的行为，这种行为来自于个体群体成员之间的相互作用以及个体互动和群体层面行为之间的关系的研究。社会动力学领域汇集了来自经济学、社会学、社会心理学和其他学科的思想，是复杂适应系统或复杂性科学的一个子领域。该领域的基本假设是，个体受到彼此行为的影响。该领域与系统动力学密切相关。像系统动力学一样，社会动力学关注的是随着时间的推移而发生的变化，并强调反馈的作用。然而，在社会动力学中，个体的选择和相互作用通常被视为总体水平行为的来源，而系统动力学则假定反馈和累积的结构负责系统水平的动力学。该领域的研究通常采取行为方法，假设个体是有限理性的，并根据当地信息采取行动。数学和计算建模是研究社会动力学的重要工具。这个领域是在20世纪40年代邓肯和卢斯等博弈论家的工作，以及数学家阿曼德 · 博雷尔的早期著作中发展起来的。由于社会动力学关注于个体层面的行为，并认识到异质性的重要性，个体，严格的分析结果往往是不可能的。相反，近似技术，如来自统计物理学的平均场近似，或计算机模拟被用来理解系统的行为。与经济学中更为传统的方法相比，研究社会动力学的学者往往对非均衡或动态行为感兴趣。也就是说，行为会随着时间的推移而改变。


Topics


See also


Notes

  1. ↑ 1.0 1.1 Durlauf, Steven; Young, Peyton (2001). Social Dynamics. Cambridge, MA: MIT Press. ISBN 0-262-04186-3. 
  2. ↑ Sterman, John (2000). Business Dynamics. McGraw Hill. ISBN 0-07-231135-5. https://archive.org/details/businessdynamics0000ster. 
  3. ↑ Luce, Duncan (1957). Games and Decisions. John Wiley & Sons, Inc.. ISBN 0486659437. https://archive.org/details/gamesdecisions00rdun. 
  4. ↑ "Brookings Institution, Center for Social Dynamics and Policy". Retrieved 29 September 2012.


References

  • Weidlich, W. (1997) "Sociodynamics applied to the evolution of urban and regional structures". Discrete Dynamics in Nature and Society, Vol. 1, pp. 85–98.

Available online: http://www.hindawi.com/GetArticle.aspx?doi=10.1155/S1026022697000101.

Available online: http://www.hindawi.com/GetArticle.aspx?doi=10.1155/S1026022697000101.

可在线阅读: http://www.hindawi.com/getarticle.aspx?doi=10.1155/s1026022697000101。


Further reading

  • Easley, David; Klienberg, Jon (2010). Networks, Crowds, and Markets. New York, NY: Cambridge University Press. ISBN 978-0-521-19533-1. 
  • Jackson, Matthew O. (2008). Social and Economic Networks. Princeton, NJ: Princeton University Press. ISBN 978-0-691-13440-6. 


External links

  • Club of Rome report, quote: "We must also keep in mind the presence of social delays--the delays necessary to allow society to absorb or to prepare for a change. Most delays, physical or social reduce the stability of the world system and increase the likelihood of the overshoot mode"
  • social-dynamics.org—Blog on Social Dynamics from Kellogg School of Management Social Dynamics Scholar

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  • Watts, D.J.

作者 Watts，d.j。; Strogatz, S.H.

2 Strogatz，s.h. (1998

1998年). "Collective dynamics of 'small-world' networks". Nature 自然》杂志. 393

第393卷 (6684

第6684期): 440–442

第440-442页. Bibcode:1998Natur.393..440W. doi:[//doi.org/10.1038%2F30918%0A%0A10.1038%20%2F%2030918 10.1038/30918 10.1038 / 30918]. PMID [//pubmed.ncbi.nlm.nih.gov/9623998

9623998 9623998 9623998]. {{cite journal}}: |access-date= requires |url= (help); Check |doi= value (help); Check |pmid= value (help); Check date values in: |accessdate= and |year= (help); Text "题目“小世界”网络的集体动态" ignored (help); line feed character in |author2= at position 15 (help); line feed character in |author= at position 12 (help); line feed character in |doi= at position 14 (help); line feed character in |issue= at position 5 (help); line feed character in |journal= at position 7 (help); line feed character in |pages= at position 9 (help); line feed character in |pmid= at position 8 (help); line feed character in |volume= at position 4 (help); line feed character in |year= at position 5 (help)

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1998 / natur. 393. . 440 w }

Category:Systems theory

范畴: 系统论

Category:Social systems

类别: 社会系统

Category:Social dynamics

类别: 社会动态


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