Berlin 2024 – scientific programme
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SOE: Fachverband Physik sozio-ökonomischer Systeme
SOE 7: Poster
SOE 7.10: Poster
Monday, March 18, 2024, 18:00–20:30, Poster D
Predicting the Dynamics of Behavioral Contagion in Human Groups with an Increment Drift-Diffusion Model — •Maryam Karimian1,2,3, Fabio Reeh1,2, and Pawel Romanczuk1,2,3 — 1Institute for Theoretical Biology, Humboldt-Universität zu Berlin — 2Science of Intelligence, Research Cluster of Excellence, Berlin — 3Bernstein Center for Computational Neuroscience, Berlin
Behavioral contagion is an interesting topic for cognitive science and collective behavior. While studies in Cognitive science overlook the impact of collective dynamics on decision processes, collective behavior studies mainly focus on simplified models of social interactions and neglect the cognitive complexity of individual agents. Hence, there is a gap in studying behavioral contagion, which incorporates not only complex individual decision processes but also concurrent social interactions that influence and are influenced by individual decisions. To address this gap, we employ a computational model to simulate virtual reality experiments (VR), unifying cognitive intricacies with collective dynamics. In this model, interaction networks are defined based on visual occupancy of agents from a first-person perspective. We aim to simulate VR experiments to explore how virtual agents responding to environmental signals influence human participants. Decision processes of participants are modeled using an extended drift-diffusion model, considering real-time updates in response to changing environmental and social signals. Our work investigates how network characteristics and temporal patterns of decision-making by virtual agents affect contagion dynamics.
Keywords: Behavioral contagion; Drift-diffusion model; Visual networks; Virtual reality experiments; Model simulations