In sociology,social complexity is aconceptual framework used in theanalysis of society. In the sciences, contemporary definitions ofcomplexity are found insystems theory, wherein thephenomenon being studied has many parts and many possible arrangements of the parts; simultaneously, what is complex and what is simple are relative and change in time.[1]
Contemporary usage of the termcomplexity specifically refers to sociologic theories of society as acomplex adaptive system, however, social complexity and itsemergent properties are recurring subjects throughout the historical development ofsocial philosophy and the study ofsocial change.[2]
Earlytheoreticians of sociology, such asFerdinand Tönnies,Émile Durkheim, andMax Weber,Vilfredo Pareto andGeorg Simmel, examined the exponential growth and interrelatedness of social encounters andsocial exchanges. The emphases on theinterconnectivity among social relationships, and the emergence of new properties within society, is found in thesocial theory produced in thesubfields of sociology.[3] Social complexity is a basis for the connection of the phenomena reported inmicrosociology andmacrosociology, and thus provides an intellectualmiddle-range for sociologists to formulate and develop hypotheses.[4][5]Methodologically, social complexity is theory-neutral, and includes the phenomena studied in microsociology and the phenomena studied in macrosociology.[2]
In 1937, the sociologistTalcott Parsons continued the work of the early theoreticians of sociology with his work onaction theory;[6] and by 1951, Parson had developed action theory into formalsystems theory inThe Social System (1951).[7] In the following decades, the synergy between generalsystems thinking and the development ofsocial system theories is carried forward byRobert K. Merton in discussions of theories of themiddle-range andsocial structure and agency. From the late 1970s until the early 1990s, sociological investigation concerned the properties of systems in which the strong correlation of sub-parts leads to the observation ofautopoetic,self-organizing,dynamical,turbulent, andchaotic behaviours that arise from mathematicalcomplexity, such as the work ofNiklas Luhmann.[8]
One of the earliest usages of the term "complexity", in thesocial andbehavioral sciences, to refer specifically to acomplex system is found in the study ofmodern organizations andmanagement studies.[9] However, particularly in management studies, the term often has been used in ametaphorical rather than in aqualitative orquantitative theoretical manner.[2] By the mid-1990s, the "complexity turn"[10] in social sciences begins as some of the same tools generally used incomplexity 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, includingconstructivist epistemology and the philosophical positions ofphenomenology,postmodernism andcritical realism.
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 thehistorical-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 analysisdifferentiated[11] by the researcher according to the level of description or explanation demanded by the research hypotheses.
At the most localized level of analysis,ethnographic,participant- or non-participant observation,content analysis and otherqualitative research methods may be appropriate. More recently, highly sophisticatedquantitative research methodologies are being developed and used in sociology at both local and globallevels of analysis. Such methods include (but are not limited to)bifurcation diagrams,network analysis,non-linear modeling, andcomputational models includingcellular automata programming,sociocybernetics and other methods ofsocial simulation.
Complexsocial network analysis is used to study the dynamics of large, complex social networks.Dynamic network analysis brings together traditionalsocial network analysis,link analysis andmulti-agent systems withinnetwork science andnetwork theory.[12] Through the use of key concepts and methods insocial network analysis,agent-based modeling, theoreticalphysics, and modernmathematics (particularlygraph theory andfractal 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 ofDuncan Watts,Albert-László Barabási,Nicholas A. Christakis,Kathleen Carley and others.
New methods of global network analysis are emerging from the work ofJohn Urry and the sociological study of globalization, linked to the work ofManuel Castells and the later work ofImmanuel Wallerstein. Since the late 1990s, Wallerstein increasingly makes use of complexity theory, particularly the work ofIlya Prigogine.[13][14][15] Dynamic social network analysis is linked to a variety of methodological traditions, above and beyondsystems thinking, includinggraph theory, traditionalsocial network analysis in sociology, andmathematical sociology. It also links tomathematical chaos andcomplex dynamics through the work ofDuncan Watts andSteven Strogatz, as well as fractal geometry throughAlbert-László Barabási and his work onscale-free networks.
The development ofcomputational sociology involves such scholars asNigel Gilbert,Klaus G. Troitzsch,Joshua M. Epstein, and others. The foci of methods in this field includesocial simulation anddata-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 ofsocionics are a variant of computational sociology.[16][17]
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 ofsymbolic interaction,exchange, andrational choice, along with the micro-level focus of computational political scientists, such asRobert Axelrod, helped to develop computational sociology'sbottom-up,agent-based approach to modeling complex systems. This is whatJoshua M. Epstein callsgenerative science.[17] Other important areas of influence includestatistics,mathematical modeling and computersimulation.
Sociocybernetics integrates sociology withsecond-order cybernetics and the work ofNiklas Luhmann, along with the latest advances incomplexity 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 tosystems thought inside and outside of sociology, specifically in the area of second-order cybernetics.
In the first decade of the 21st century, the diversity of areas of application has grown[19] as more sophisticated methods have developed. Social complexity theory is applied in studies of socialcooperation andpublic goods;[20]altruism;[21]education;[22] global civil society[23]collective action andsocial movements;[24][25]social inequality;[26] workforce andunemployment;[27][28]policy analysis;[29][30]health care systems;[31] andinnovation andsocial change,[32][33] to name a few. A current international scientific research project, theSeshat: Global History Databank, was explicitly designed to analyze changes in social complexity from theNeolithic Revolution until theIndustrial Revolution.
As amiddle-range theoretical platform, social complexity can be applied to any research in whichsocial interaction or the outcomes of such interactions can be observed, but particularly where they can bemeasured and expressed ascontinuous ordiscrete data points. One common criticism often cited regarding the usefulness of complexity science in sociology is the difficulty of obtaining adequate data.[34] 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. Fromchildhood friendships andteen pregnancy[2] tocriminology[35] andcounter-terrorism,[36] theories of social complexity are being applied in almost allareas of sociological research.
In the area ofcommunications research andinformetrics, the concept of self-organizing systems appears in mid-1990s research related to scientific communications.[37]Scientometrics andbibliometrics are areas of research in which discrete data are available, as are several other areas of social communications research such associolinguistics.[2] Social complexity is also a concept used insemiotics.[38]
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