Computational sociology
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Computational sociology is the branch of sociology that uses computationally intensive methods to analyze and model social phenomena. Using computer simulations, artificial intelligence, complex statistical methods, & analytic approaches like social network analysis, computational sociology develops and tests theories of complex social processes through bottom-up modeling of social interactions.
It involves the apprehension of social agents, the interaction among these agents, and the issue of these interactions on the social aggregate. Although the planned matter and methodologies in social science differ from those in natural science or computer science, several of the approaches used in sophisticated social simulation originated from fields such(a) as physics and artificial intelligence. Some of the approaches that originated in this field construct been imported into the natural sciences, such(a) as measures of network centrality from the fields of social network analysis and network science.
In relevant literature, computational sociology is often related to the study of social complexity. Social complexity view such as complex systems, non-linear interconnection among macro and micro process, and emergence, cause entered the vocabulary of computational sociology. A practical and well-known example is the construction of a computational framework in the form of an "artificial society", by which researchers can analyze the an arrangement of parts or elements in a particular form figure or combination. of a social system.