A novel interdisciplinary approach to socio-technical complexity. Sociologically-driven, computable methods for sport spectator crowds' semi-supervised analysis

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.