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Computational social science

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Abstract The social sciences investigate human and social dynamics and organization at all levels of analysis (consilience), including cognition, decision making, behavior, groups, organizations, societies, and the world system. Computational social science is the integrated, interdisciplinary pursuit of social inquiry with emphasis on information processing and through the medium of advanced computation. The main computational social science areas are automated information extraction systems, social network analysis, social geographic information systems (GIS), complexity modeling, and social simulation models. Just like Galileo exploited the telescope as the key instrument for observing and gaining a deeper and empirically truthful understanding of the physical universe, computational social scientists are learning to exploit the advanced and increasingly powerful instruments of computation to see beyond the visible spectrum of more traditional disciplinary analyses. Copyright © 2010 John Wiley & Sons, Inc. This article is categorized under: Data: Types and Structure > Social Networks

A normal (bell‐shaped) distribution (a) and a power law (b). Besides differing in the lower range (left tail), the power law (b) also produces much more likely extreme events (right tail), such as severe terrorist events, political collapse, or other extreme social events. Source for the graphs: Wikipedia.

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Agent‐based models. (a) Cooperative target observation; (b) group dynamics in a changing environment; (c) ethno‐sectarian integration in a bicultural society; and (d) emergence of segregation caused by violence. Sources: (a) Sullivan et al.131; (b) Cioffi et al.132; and (c)‐(d) Luke et al.,133 based on Schelling.100.

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System dynamics models of (a) innovation processes, (b) strategic rivalry, and (c) the MIT model of polity dynamics. Sources: (a) System Dynamics Society website, (b) prepared by the author based on the Richardson's124 arms race model, and (c) Choucri et al.125.

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