In sociology, social complexity is a conceptual framework used in the analysis of society. In the sciences, contemporary definitions of complexity are found in systems theory, wherein the phenomenon 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.
Contemporary usage of the term complexity specifically refers to sociologic theories of society as a complex adaptive system, however, social complexity and its emergent properties are recurring subjects throughout the historical development of social philosophy and the study of social change.
Early theoreticians of sociology, such as Ferdinand Tönnies, Émile Durkheim, and Max Weber, Vilfredo Pareto and Georg Simmel, examined the exponential growth and interrelatedness of social encounters and social exchanges. The emphases on the interconnectivity among social relationships, and the emergence of new properties within society, is found in the social theory produced in the subfields of sociology. Social complexity is a basis for the connection of the phenomena reported in microsociology and macrosociology, and thus provides an intellectual middle-range for sociologists to formulate and develop hypotheses. Methodologically, social complexity is theory-neutral, and includes the phenomena studied in microsociology and the phenomena studied in macrosociology.
In 1937, the sociologist Talcott Parsons continued the work of the early theoreticians of sociology with his work on action theory; and by 1951, Parson had developed action theory into formal systems theory in The Social System (1951). In the following decades, the synergy between general systems thinking and the development of social system theories is carried forward by Robert K. Merton in discussions of theories of the middle-range and social structure and agency.
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This is a seminar course. By reading and discussing an introductory book as well as research papers about computational social science, students will become familiar with core issues and techniques in
Students learn about advanced topics in machine learning, artificial intelligence, optimization, and data science. Students also learn to interact with scientific work, analyze and understand strength
Ce cours constitue une introduction à l'étude sociale et culturelle des questions architecturales et urbaines. Il vise à familiariser l'étudiant-e avec les concepts et les méthodes des sciences social
Sociology is a social science that focuses on society, human social behavior, patterns of social relationships, social interaction, and aspects of culture associated with everyday life. In simple words sociology is the scientific study of society. It uses various methods of empirical investigation and critical analysis to develop a body of knowledge about social order and social change. While some sociologists conduct research that may be applied directly to social policy and welfare, others focus primarily on refining the theoretical understanding of social processes and phenomenological method.
An agent-based model (ABM) is a computational model for simulating the actions and interactions of autonomous agents (both individual or collective entities such as organizations or groups) in order to understand the behavior of a system and what governs its outcomes. It combines elements of game theory, complex systems, emergence, computational sociology, multi-agent systems, and evolutionary programming. Monte Carlo methods are used to understand the stochasticity of these models.
A complex adaptive system is a system that is complex in that it is a dynamic network of interactions, but the behavior of the ensemble may not be predictable according to the behavior of the components. It is adaptive in that the individual and collective behavior mutate and self-organize corresponding to the change-initiating micro-event or collection of events. It is a "complex macroscopic collection" of relatively "similar and partially connected micro-structures" formed in order to adapt to the changing environment and increase their survivability as a macro-structure.
Explores the principles of modularity and abstraction in computer systems design, emphasizing their role in simplifying complex systems and improving scalability.
We develop an algorithm to solve the bottleneck assignment problem (BAP) that is amenable to having computation distributed over a network of agents. This consists of exploring how each component of the algorithm can be distributed, with a focus on one com ...
According to physicalism, everything is physical or metaphysically connected to the physical. If physicalism were true, it seems that we should - in principle - be able to reduce the descriptions and explanations of special sciences to physical ones, for e ...
Dordrecht2023
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Accurately predicting weather and climate in cities is critical for safeguarding human health and strengthening urban resilience. Multimodel evaluations can lead to model improvements; however, there have been no major intercomparisons of urban-focussed la ...