Abstract
It is known that crowds as spontaneous aggregations of people have been studied from as early as XIX century. Today these investigations have advanced to the point where scholars are trying to not only observe and analyze crowds, but also simulate those using computational methods. As a result, a distinct area of research emerged that draws expertise from various subject fields – crowd modeling. Though the applicability of crowd modeling is widely acknowledged, the conceptual development of the area received rather scarce attention. It seems that it has so far been developing as an area predominantly driven by the aim of informing the practice of planners and decision makers. In this paper, we examine the current state of affairs in a distinct branch of crowd modeling that focuses on groups of people other than individuals as key actors within the crowd. We argue that crowd modeling can be effectively used to facilitate not only for prediction, but also allows to deepen theoretical understanding of the crowds as collectives of people that are complex, contextually embedded and consist of dynamic entities that impose certain logics of behavior.
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This paper is financially supported by Russian Foundation for Basic Research, research project No. 16-36-00367 mol_a, project ID: 116021210004
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Voloshin, D., Puzyreva, K., Derevitsky, I., Karbovskii, V. (2016). Groups and Collectivities in Crowd Modeling: Critical Evaluation of the State-of-the-Art and Suggestions for Further Studies. In: Chugunov, A., Bolgov, R., Kabanov, Y., Kampis, G., Wimmer, M. (eds) Digital Transformation and Global Society. DTGS 2016. Communications in Computer and Information Science, vol 674. Springer, Cham. https://doi.org/10.1007/978-3-319-49700-6_49
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DOI: https://doi.org/10.1007/978-3-319-49700-6_49
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