Social and spatial predictors of collective search behaviors - Marion Hoffman; Tyler Thrash; Christoph Hölscher; Mubbasir Kapadia; Victor R. Schinazi (Scientific Reports)
Abstract Understanding crowd behavior is critical for designing buildings and public spaces with efficient circulation. However, the interplay of social and spatial contexts makes this endeavor challenging. This paper examines scenarios in which crowds perform a search task with time constraints, akin to individuals shopping or officers searching a crime area. We formulate and test two sets of hypotheses defined at the crowd and individual levels using desktop VR experiments. We conducted four experimental sessions that employed different social incentives (collaborative versus competitive) with a total of 140 participants, using a mixed factorial design where each individual participated in 12 trials. We found that competitive incentives produced higher levels of crowd aggregation than collaborative incentives. In addition, individuals were more likely to be influenced by others’ behaviors in the collaborative compared to the competitive condition. Notably, these social signals were conveyed among participants without any verbal communication. We also developed a novel graph theoretic measure, “search attractiveness,” that accurately predicts space occupation during a search task. This paper highlights the roles of social and spatial contexts in understanding occupation and aggregation.