Computational sociology is a branch of sociology that uses computationally intensive methods to analyze and model social phenomena. The technology is widely used in government, national security and intelligence applications and also in research, commerce, and medicine. Using computer simulations, artificial intelligence, complex statistical methods, and 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 understanding of social agents, the interaction among these agents, and the effect of these interactions on the social aggregate. Regarding the behaviors of populations as complex interactions between individuals allows us to use arithmetic models and experimental populations in order to evaluate a society’s performance. Although the subject matter and methodologies in social science differ from those in natural science or computer science, several of the approaches used in contemporary social simulation originated from fields such as physics and artificial intelligence. Data from millions of digital social interactions and new arithmetic techniques map out the processes through which desirable and undesirable behavior comes into being in populations. Some of the approaches that originated in this field have been imported into the natural sciences, such as measures of network centrality from the fields of social network analysis and network science. However, these techniques give rise to significant ethical issues (Google has launched DeepMind for the development of AI; Facebook has developed DeepFace (facial recognition in 97% of cases, just like a human being)).
The world of science has undergone a major transformation by virtue of technological innovations in computing and information processing. In the relevant literature, computational sociology is often related to the study of social complexity. Social complexity concepts such as complex systems, non-linear interconnection among macro and micro process, and emergence, have entered the vocabulary of computational sociology. Computational social science exists at the intersection of these varied disciplines, offering a wide range of tools and research methodologies that were previously not available to social and behavioral scientists. Computational social scientists from computer science and physics often see as their main task to establish empirical regularities which they view as “social laws.” A practical and well-known example is the construction of a computational model in the form of an “artificial society”, by which researchers can analyze the structure of a social system.