A fuzzy ontology for the classification of crowds at concerts

The paper presents a fuzzy ontology for the classification of crowds according to existing theories from social sciences and bottom- up computational approaches. The behavior and dynamics of crowds can be studied as resulting from the behavior of huge numbers of individuals taking part to it and, even if theories on crowd behavior are still open issues for several disciplines, we refer to Elias Canetti's theory on masses, one of the most known and explanatory of crowds behaviors and dynamics. This work is part of an ongoing research project whose goal is the development of decision support systems to design and manage public spaces and events. In particular, we focus here to a collaboration with the famous Italian singer Lorenzo Cherubini and his band, whose aim is to develop formal and computational tools for the classification of different crowd phenomenology that can appear during rock concerts. One of the main contribution of this work is towards knowledge sharing and exchange, since several experiences but also software platforms are nowadays available that could better support the study, e.g. through simulation, of crowd behavior and dynamics