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A Novel Interdisciplinary Approach to Socio-Technical Complexity

Sociologically Driven, Computable Methods for Sport-Spectator Crowds’ Semi-Supervised Analysis

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New Frontiers in the Study of Social Phenomena

Abstract

The chapter presents a novel interdisciplinary approach that integrates micro-sociological analysis into computer-vision and pattern-recognition modeling and algorithms, the purpose being to tackle socio-technical complexity at a systemic yet micro-grounded level. The approach is empirically-grounded and both theoretically- and analytically-driven, yet systemic and multidimensional, semi-supervised and computable, and oriented towards large scale applications. The chapter describes the proposed approach especially as for its sociological foundations, and as applied to the analysis of a particular setting --i.e. sport-spectator crowds. Crowds, better defined as large gatherings, are almost ever-present in our societies, and capturing their dynamics is crucial. From social sciences to public safety management and emergency response, modeling and predicting large gatherings' presence and dynamics, thus possibly preventing critical situations and being able to properly react to them, is fundamental. This is where semi/automated technologies can make the difference. The work presented in this chapter is intended as a scientific step towards such an objective.

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Notes

  1. 1.

    http://www.loa.istc.cnr.it/projects/viscoso.

  2. 2.

    We tried the integration of micro-sociology and computer vision also with respect to the analysis and detection of “free-standing conversational groups” and “facing formation” (Setti et al., 2015).

  3. 3.

    On gender and bodily conduct see also, e.g., Young (1980) and Guillaumin (1992).

  4. 4.

    “A persistent and popular view holds that high population density inevitably leads to violence. This myth, which is based on rat research, applies neither to us nor to other primates” (de Waal et al. 2000, p. 77).

  5. 5.

    Verbal conduct (e.g., chorus) is highly relevant in facilitating and enhancing intra-audience coordination and synchrony, yet it has not been considered here given the technical characteristics of the dataset.

  6. 6.

    You can find the annotation manual equipped with visual examples of each atomic component at the following address: http://mmlab.disi.unitn.it/extra/oz/.

  7. 7.

    If A is engaged in an action of the satisfaction ensemble, and B, next (or near) to the former in the stands, is engaged in an action of the dissatisfaction, or the disengagement ensembles, we can fairly assume they do not belong to the same fan group. If instead B is engaged in cheering—depending on how many people around A and B are doing something labeled as cheering or satisfaction —often, they belong to the same fan group.

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Acknowledgments

Besides all members of the OZ project, I wish to thank Marco Cristani, Roberta Ferrario and Daniele Porello for the helpful discussions about compositional methods to be axiomatized and computed.

Funding Acknowledgments

This work is part of the OZ project, financed by the Winter Universiade Trentino 2013 Educational Programme. Chiara Bassetti is supported by the VisCoSo project grant, funded by the Autonomous Province of Trento through the “Team 2011” programme.

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  1. Laboratory for Applied Ontology, Institute of Cognitive Sciences and Technologies – CNR, Via alla Cascata 56 C, 38123, Trento, Italy

    Dr. Chiara Bassetti Ph.D.

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  1. Institute of Cognitive Science and Technology – CNR, Rome, Italy

    Federico Cecconi

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Bassetti, C. (2016). A Novel Interdisciplinary Approach to Socio-Technical Complexity. In: Cecconi, F. (eds) New Frontiers in the Study of Social Phenomena. Springer, Cham. https://doi.org/10.1007/978-3-319-23938-5_7

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