“社会复杂性”的版本间的差异

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In sociology, social complexity is a conceptual framework used in the analysis of society. Contemporary definitions of complexity in the sciences are found in relation to systems theory, in which a phenomenon under study has many parts and many possible arrangements of the relationships between those parts. At the same time, what is complex and what is simple is relative and may change with time.[1]

Current usage of the term "complexity" in the field of sociology typically refers specifically to theories of society as a complex adaptive system. However, social complexity and its emergent properties are central recurring themes throughout the historical development of social thought and the study of social change.[2] The early founders of sociological theory, such as Ferdinand Tönnies, Émile Durkheim, Max Weber, Vilfredo Pareto, and Georg Simmel, all examined the exponential growth and increasing interrelatedness of social encounters and exchanges. This emphasis on interconnectivity in social relationships and the emergence of new properties within society is found in theoretical thinking in multiple areas of sociology.[3] As a theoretical tool, social complexity theory serves as a basis for the connection of micro- and macro-level social phenomena, providing a meso-level or middle-range theoretical platform for hypothesis formation.[4][5] Methodologically, the concept of social complexity is theory-neutral, meaning that it accommodates both local (micro) and global (macro) phenomena in sociological research.[2]

Theoretical background

Illustration of complexity (Penrose tiling fractal)

The American sociologist Talcott Parsons carried on the work of the early founders mentioned above in his early (1937) work on action theory.[6] By 1951, Parsons places these earlier ideas firmly into the realm of formal systems theory in The Social System.[7] For the next several decades, this synergy between general systems thinking and the further development of social system theories is carried forward by Parson's student, Robert K. Merton, and a long line of others, in discussions of theories of the middle-range and social structure and agency. During part of this same period, from the late 1970s through the early 1990s, discussion ensues in any number of other research areas about the properties of systems in which strong correlation of sub-parts leads to observed behaviors variously described as autopoetic, self-organizing, dynamical, turbulent, and chaotic. All of these are forms of system behavior arising from mathematical complexity. By the early 1990s, the work of social theorists such as Niklas Luhmann[8] began reflecting these themes of complex behavior.

One of the earliest usages of the term "complexity", in the social and behavioral sciences, to refer specifically to a complex system is found in the study of modern organizations and management studies.[9] However, particularly in management studies, the term often has been used in a metaphorical rather than in a qualitative or quantitative theoretical manner.[2] By the mid-1990s, the "complexity turn"[10] in social sciences begins as some of the same tools generally used in complexity science are incorporated into the social sciences. By 1998, the international, electronic periodical, Journal of Artificial Societies and Social Simulation, had been created. In the last several years, many publications have presented overviews of complexity theory within the field of sociology. Within this body of work, connections also are drawn to yet other theoretical traditions, including constructivist epistemology and the philosophical positions of phenomenology, postmodernism and critical realism.

方法论

Methodologically, social complexity is theory-neutral, meaning that it accommodates both local and global approaches to sociological research.[2] The very idea of social complexity arises out of the historical-comparative methods of early sociologists; obviously, this method is important in developing, defining, and refining the theoretical construct of social complexity. As complex social systems have many parts and there are many possible relationships between those parts, appropriate methodologies are typically determined to some degree by the research level of analysis differentiated[11] by the researcher according to the level of description or explanation demanded by the research hypotheses.


从方法上讲，社会复杂性这一特征是无关乎于理论的，这意味着无论是地方性（局部）或全球性（全局）社会学研究都将适用。社会复杂性的想法源于早期社会学家的历史比较方法。显然，这种方法对于发展，定义和完善社会复杂性的理论构造非常重要。由于复杂社会系统包含了许多部分，而且这些部分之间又存在许多可能的关系。因此不同的适用方法在一定程度上取决于不同的分析研究深度【地方性（局部）或全球性（全局）】，再进一步说，便是由研究人员根据研究假设所要求的描述或解释程度来区分。


At the most localized level of analysis, ethnographic, participant- or non-participant observation, content analysis and other qualitative research methods may be appropriate. More recently, highly sophisticated quantitative research methodologies are being developed and used in sociology at both local and global levels of analysis. Such methods include (but are not limited to) bifurcation diagrams, network analysis, non-linear modeling, and computational models including cellular automata programming, sociocybernetics and other methods of social simulation.


在地方性（局部）分析中，人种志研究（也称作人类学研究或民族志研究）观察法，参与或非参与观察法，内容分析法和其他定性研究方法可能比较合适。近日，同时适用于地方性（局部）和全球性（全局）的社会学研究法正在开发使用中，它是具有高度复杂的定量研究方法。这样的方法包括（但不限于）分岔图法，网络分析法和非线性建模法；以及包括元胞自动机编程，社会控制论和其他社会仿真在内的计算建模法。


复杂社交网络分析法

Main article: Dynamic network analysis

Complex social network analysis is used to study the dynamics of large, complex social networks. Dynamic network analysis brings together traditional social network analysis, link analysis and multi-agent systems within network science and network theory.[12] Through the use of key concepts and methods in social network analysis, agent-based modeling, theoretical physics, and modern mathematics (particularly graph theory and fractal geometry), this method of inquiry brought insights into the dynamics and structure of social systems. New computational methods of localized social network analysis are coming out of the work of Duncan Watts, Albert-László Barabási, Nicholas A. Christakis, Kathleen Carley and others.


复杂社交网络分析法用于研究大型复杂社交网络的动态系统（动力学）。其动态网络分析法将网络科学和网络理论中传统的社交网络分析法，链接分析法以及多主体系统结合在一起。通过运用社交网络分析，基于主体的建模，理论物理学和现代数学（尤其是图论和分形几何）中的关键概念和方法，为社会系统的动力学和结构带来了深入见解。通过Duncan Watts，Albert-LászlóBarabási，Nicholas A. Christakis，Kathleen Carley等人的工作，总结出了全新的地方性（局部）社交网络分析计算方法。


New methods of global network analysis are emerging from the work of John Urry and the sociological study of globalization, linked to the work of Manuel Castells and the later work of Immanuel Wallerstein. Since the late 1990s, Wallerstein increasingly makes use of complexity theory, particularly the work of Ilya Prigogine.[13][14][15] Dynamic social network analysis is linked to a variety of methodological traditions, above and beyond systems thinking, including graph theory, traditional social network analysis in sociology, and mathematical sociology. It also links to mathematical chaos and complex dynamics through the work of Duncan Watts and Steven Strogatz, as well as fractal geometry through Albert-László Barabási and his work on scale-free networks.


通过约翰·乌里（John Urry）的工作，加上全球性网络中的学者们对社会学的研究，不断涌现出新的全球性网络分析方法，这些方法同时与曼努埃尔·卡斯特尔（Manuel Castells）的工作以及伊曼纽尔·沃勒斯坦（Immanuel Wallerstein）的后续工作相关。自1990年代后期以来，Wallerstein越来越多地利用复杂性理论，尤其是Ilya Prigogine的著作。动态社会网络分析与系统思想之外的各种传统方法学相关，包括图论，社会学中的传统社会网络分析和数学社会学。它还通过Duncan Watts和Steven Strogatz的研究与混沌数学和复杂动力学联系在一起，并通过Albert-László Barabási和他在无标度网络上的研究成果发展出分形几何法。

计算社会学

Main article: Computational sociology

The development of computational sociology involves such scholars as Nigel Gilbert, Klaus G. Troitzsch, Joshua M. Epstein, and others. The foci of methods in this field include social simulation and data-mining, both of which are sub-areas of computational sociology. Social simulation uses computers to create an artificial laboratory for the study of complex social systems; data-mining uses machine intelligence to search for non-trivial patterns of relations in large, complex, real-world databases. The emerging methods of socionics are a variant of computational sociology.[16][17]


计算社会学的发展涉及到以下学者的研究：奈杰尔·吉尔伯特（Nigel Gilbert），克劳斯·G·特罗伊茨（Klaus G.Troitzsch），约书亚·爱泼斯坦（Joshua M.Epstein）等。该领域研究的方法的集中包括社会仿真和数据挖掘，它们都是计算社会学的子领域。 社会仿真运用计算机创建一个用于研究复杂社会系统的人工实验室；数据挖掘则运用机器智能，在大型、复杂的真实世界数据库中搜索其之间联系的关键点（斑图）。全新的社会人格学方法是计算社会学的一种变体。


Computational sociology is influenced by a number of micro-sociological areas as well as the macro-level traditions of systems science and systems thinking. The micro-level influences of symbolic interaction, exchange, and rational choice, along with the micro-level focus of computational political scientists, such as Robert Axelrod, helped to develop computational sociology's bottom-up, agent-based approach to modeling complex systems. This is what Joshua M. Epstein calls generative science.[17] Other important areas of influence include statistics, mathematical modeling and computer simulation.

计算社会学受到许多微观社会学领域以及系统科学和系统思维的宏观传统的影响。符号互动理论，社会交换理论和理性选择理论的微观影响，以及罗伯特·阿克塞尔罗德（Robert Axelrod）等计算政治学家的微观中心思想，共同促进了计算社会学自下而上，基于主体建模方法的发展，进而研究于复杂系统。这就是约书亚·爱泼斯坦（Joshua M. Epstein）所称的生成科学。

社会控制论

Main article: Sociocybernetics

Sociocybernetics integrates sociology with second-order cybernetics and the work of Niklas Luhmann, along with the latest advances in complexity science. In terms of scholarly work, the focus of sociocybernetics has been primarily conceptual and only slightly methodological or empirical.[18] Sociocybernetics is directly tied to systems thought inside and outside of sociology, specifically in the area of second-order cybernetics.


社会控制论将社会学与二阶控制论和尼古拉斯·卢曼（Niklas Luhmann）的工作结合在一起，并结合了复杂性科学的最新成果。在学术研究方面，社会控制论偏重于概念性，弱于方法论或经验实践。社会控制论与社会学内外系统直接相关，特别是在二阶控制论领域。

应用与分支

Areas of application

As a middle-range theoretical platform, social complexity can be applied to any research in which social interaction or the outcomes of such interactions can be observed, but particularly where they can be measured and expressed as continuous or discrete data points. One common criticism often cited regarding the usefulness of complexity science in sociology is the difficulty of obtaining adequate data.[19] Nonetheless, application of the concept of social complexity and the analysis of such complexity has begun and continues to be an ongoing field of inquiry in sociology. From childhood friendships and teen pregnancy[2] to criminology[20] and counter-terrorism,[21] theories of social complexity are being applied in almost all areas of sociological research.

As a middle-range theoretical platform, social complexity can be applied to any research in which social interaction or the outcomes of such interactions can be observed, but particularly where they can be measured and expressed as continuous or discrete data points. One common criticism often cited regarding the usefulness of complexity science in sociology is the difficulty of obtaining adequate data.[67] Nonetheless, application of the concept of social complexity and the analysis of such complexity has begun and continues to be an ongoing field of inquiry in sociology. From childhood friendships and teen pregnancy[58] to criminology[68] and counter-terrorism,[69] theories of social complexity are being applied in almost all areas of sociological research.

作为一个中等规模的理论平台，社会复杂性可以应用于任何社会互动或可以观察到这种互动的结果的研究，只需要相关的数据可以用连续或者离散的点来表示即可。 关于复杂性科学在社会学中的应用，一个常见的批判问题就是很难获得足够的数据。 [67]尽管如此，社会复杂性概念的应用以及对这种复杂性的分析已经开始并将继续成为社会学研究的必要研究领域。 从儿时的友谊和少女怀孕到犯罪学和反恐怖主义，社会复杂性理论几乎应用于社会学研究的所有方面。


In the area of communications research and informetrics, the concept of self-organizing systems appears in mid-1990s research related to scientific communications.[22] Scientometrics and bibliometrics are areas of research in which discrete data are available, as are several other areas of social communications research such as sociolinguistics.[2] Social complexity is also a concept used in semiotics.[23]

In the area of communications research and informetrics, the concept of self-organizing systems appears in mid-1990s research related to scientific communications.[70] Scientometrics and bibliometrics are areas of research in which discrete data are available, as are several other areas of social communications research such as sociolinguistics.[58] Social complexity is also a concept used in semiotics.[71]

在通信研究和信息计量学领域，自组织系统的概念出现在20世纪90年代中期与科学通信有关的研究中，主要得益于科学计量学，文献计量学，社会语言学都是可以获得离散数据的研究领域， [58]社会复杂性也是符号学中使用的一个概念。 [71]

社会复杂性最初出现在20世纪90年代通信研究和信息计量学领域，自组织系统的概念首先出现在科学通信有关的研究，主要得益于科学计量学，文献计量学，社会语言学都是可以有离散的数据，[58]社会复杂性也是符号学中最初使用的一个概念。 [71]


In the first decade of the 21st century, the diversity of areas of application has grown[24] as more sophisticated methods have developed. Social complexity theory is applied in studies of social cooperation and public goods;[25] altruism;[26] voting behavior;[27][28] education;[29] global civil society [30] and global civil unrest;[31] collective action and social movements;[32][33] social inequality;[34] workforce and unemployment;[35][36] economic geography and economic sociology;[37] policy analysis;[38][39] health care systems;[40] and innovation and social change,[41][42] to name a few. A current international scientific research project, the Seshat: Global History Databank, was explicitly designed to analyze changes in social complexity from the Neolithic Revolution until the Industrial Revolution.

In the first decade of the 21st century, the diversity of areas of application has grown[72] as more sophisticated methods have developed. Social complexity theory is applied in studies of social cooperation and public goods;[73] altruism;[74] voting behavior;[75][76] education;[77] global civil society [78] and global civil unrest;[79] collective action and social movements;[80][81] social inequality;[82] workforce and unemployment;[83][84] economic geography and economic sociology;[85] policy analysis;[86][87] health care systems;[88] and innovation and social change,[89][90] to name a few. A current international scientific research project, the Seshat: Global History Databank, was explicitly designed to analyze changes in social complexity from the Neolithic Revolution until the Industrial Revolution.

在21世纪的第一个十年，随着方法的发展应用领域也在不断增加。 社会复杂性理论应用于社会研究的各个方面，包括社会合作和公共产品的研究，利他主义，投票行为，教育，全球社会动乱，集体行动和社会运动，社会不平等，劳动力和失业，经济地理和经济社会学，政策分析，卫生健康系统，创新和社会变革等等。 当前的一个国际科学研究项目，Seshat: 全球历史数据库，被明确地设计用来分析从新石器革命到工业革命的社会复杂性的变化。

See also

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Social science

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General

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References

  1. ↑ Waldrop, M. Mitchell (1992.) Complexity: The Emerging Science at the Edge of Order and Chaos. New York, NY: Simon & Schuster.
  2. ↑ 2.0 2.1 2.2 2.3 2.4 2.5 Eve, Raymond, Sara Horsfall and Mary E. Lee (eds.) (1997). Chaos, Complexity and Sociology: Myths, Models, and Theories. Thousand Oaks, CA: Sage Publications.
  3. ↑ Giddens, Anthony (1979). Central problems in Social Theory: Action, Structure and Contradiction in Social Analysis. London: Macmillan.
  4. ↑ Freese, Lee (1980). "Formal Theorizing." Annual Review of Sociology, 6: 187–212 (August 1980).
  5. ↑ Cohen, B. P. (1989). Developing sociological knowledge: theory and method (2nd ed.). Chicago: Nelson–Hall.
  6. ↑ Parsons, Talcott ([1937] 1949). The Structure of Social Action: A Study in Social Theory with Special Reference to a Group of European Writers. New York, NY: The Free Press.
  7. ↑ Parsons, Talcott (1951). The Social System. New York, NY: The Free Press
  8. ↑ Luhmann, Niklas (1990.) Essays on Self-Reference, New York: Columbia University Press.
  9. ↑ Kiel, L. Douglas (1994). Managing Chaos and Complexity in Government: A New Paradigm for Managing Change, Innovation and Organizational Renewal. Jossey-Bass: San Francisco.
  10. ↑ Urry, John (2005). "The Complexity Turn." Theory, Culture and Society, 22(5): 1–14.
  11. ↑ Luhmann, Niklas (1982). The Differentiation of Society. New York, NY: Columbia University Press.
  12. ↑ Carley, Kathleen M. (2003), "Dynamic Network Analysis." Dynamic Social Network Modeling and Analysis: Workshop Summary and Papers, Ronald Breiger, Kathleen Carley, and Philippa Pattison (eds.), National Research Council (Committee on Human Factors): Washington, D.C.: 133–145.
  13. ↑ Barabási, Albert-László (2003). Linked: The New Science of Networks. Cambridge, MA: Perseus Publishing.
  14. ↑ Freeman, Linton C. (2004). The Development of Social Network Analysis: A Study in the Sociology of Science. Vancouver Canada: Empirical Press.
  15. ↑ Watts, Duncan J. (2004). "The New Science of Networks." Annual Review of Sociology, 30: 243–270.
  16. ↑ Gilbert, Nigel and Klaus G. Troitzsch (2005). Simulation for Social Scientists, 2nd Edition. New York, NY: Open University Press.
  17. ↑ 17.0 17.1 Epstein, Joshua M. (2007). Generative Social Science: Studies in Agent-Based Computational Modeling. Princeton, NJ: Princeton University Press.
  18. ↑ Geyer, Felix and Johannes van der Zouwen (1992). "Sociocybernetics." Handbook of Cybernetics, C.V. Negoita (ed.): 95–124. New York: Marcel Dekker.
  19. ↑ Stewart, Peter (2001). "Complexity Theories, Social Theory, and the Question of Social Complexity." Philosophy of the Social Sciences, 31(3): 323–360.
  20. ↑ Lee, Ju-Sung. (2001). "Evolving Drug Networks." Carnegie Mellon Center for Computational Analysis of Social and Organizational Systems (CASOS) Conference Presentation (unpublished).
  21. ↑ Carley, Kathleen (2003). "Destabilizing Terrorist Networks." Proceedings of the 8th International Command and Control Research and Technology Symposium. Conference held at the National Defense War College: Washington D.C., Evidence Based Research, Track 3. (Electronic Publication). -{zh-cn:互联网档案馆; zh-tw:網際網路檔案館; zh-hk:互聯網檔案館;}-的存檔，存档日期2004-12-18.
  22. ↑ Leydesdorff, Loet (1995). The Challenge of Scientometrics: The development, measurement, and self-organization of scientific communications. Leiden: DSWO Press, Leiden University.
  23. ↑ Dimitrov, Vladimir and Robert Woog (1997). "Studying Social Complexity: From Soft to Virtual Systems Methodology." Complex Systems, 11:(6).
  24. ↑ Saberi, Mohammad Karim, Alireza Isfandyari-Moghaddam and Sedigheh Mohamadesmaeil (2011). "Web Citations Analysis of the JASSS: the First Ten Years." Journal of Artificial Societies and Social Simulation, 14:(4), 22.
  25. ↑ Nowak, Martin and Roger Highfield (2011). Super Cooperators: Altruism, Evolution, and Why We Need Each Other to Succeed. New York, NY: Free Press.
  26. ↑ Hang, Ye, Fei Tan, Mei Ding, Yongmin Jia and Yefeng Chen (2011). "Sympathy and Punishment: Evolution of Cooperation in Public Goods Game." Journal of Artificial Societies and Social Simulation, 14(4): 20.
  27. ↑ Braha, D., & de Aguiar, M. A. (2016). Voting Contagion. arXiv preprint arXiv:1610.04406.
  28. ↑ Braha, D., & de Aguiar, M. A. (2017). Voting contagion: Modeling and analysis of a century of U.S. presidential elections. PLoS ONE 12(5): e0177970. https://doi.org/10.1371/journal.pone.0177970
  29. ↑ Mason, Mark (2008). Complexity Theory and the Philosophy of Education. Hoboken, NJ: Wiley-Blackwell (Educational Philosophy and Theory Special Issues).
  30. ↑ Castellani, Brian. (2018). "The Defiance of Global Commitment: A Complex Social Psychology. Routledge complexity in social science series." doi:10.4324/9781351137140.
  31. ↑ Braha, Dan. (2012). "Global Civil Unrest: Contagion, Self-Organization, and Prediction." PLoS ONE 7(10): e48596. doi:10.1371/journal.pone .0048596.
  32. ↑ Lohmann Susanne (1994). "Dynamics of Informational Cascades: The Monday Demonstrations in Leipzig, East Germany, 1989–1991," World Politics, 47: 42–101.
  33. ↑ Chesters, Graeme and Ian Welsh (2006). Complexity and Social Movements: Protest at the Edge of Chaos." London: Routledge (International Library of Sociology).
  34. ↑ Castellani, Brian et al. (2011). "Addressing the U.S. Financial/Housing Crisis: Pareto, Schelling and Social Mobility."Working Paper.
  35. ↑ Hedström, Peter and Yvonne Åberg (2011). "Social interaction and youth unemployment." Analytical Sociology and Social Mechanisms, Pierre Demeulenaere (ed.). Cambridge: Cambridge University Press.
  36. ↑ Yilmaz, Levent (2011). "Toward Multi-Level, Multi-Theoretical Model Portfolios for Scientific Enterprise Workforce Dynamics." Journal of Artificial Societies and Social Simulation, 14(4): 2.
  37. ↑ Dan Braha, Blake Stacey and Yaneer Bar-Yam. (2011). "Corporate Competition: A Self-Organizing Network." Social Networks, 33(3): 219-230.
  38. ↑ Jervis, Robert (1998). System Effects: Complexity in Political and Social Life. Princeton, NJ: Princeton University Press.
  39. ↑ Elliott, Euel and L. Douglas Kiel (eds.) (2000). Nonlinear Dynamics, Complexity and Public Policy. Hauppauge NY: Nova Science Publishers.
  40. ↑ Brian Castellani, Rajeev Rajaram, J. Galen Buckwalter, Michael Ball and Frederic Hafferty (2012). "Place and Health as Complex Systems: A Case Study and Empirical Test". SpringerBriefs in Public Health.
  41. ↑ Leydesdorff, Loet (2006). The Knowledge-Based Economy Modeled, Measured, Simulated. Boca Raton, FL: Universal-Publishers .
  42. ↑ Lane, D.; Pumain, D.; Leeuw, S.E. van der; West, G. (eds.) (2009). Complexity Perspectives in Innovation and Social Change. New York, NY: Springer (Methodos Series, Vol. 7).

Further reading

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