Information spreading in mixed groups in aircraft cabins with face-to-face interaction

The spread of information through face-to-face contacts among distinct passenger groups in the confined, dynamic environment of commercial aircraft cabins is critical for service quality, yet our understanding remains largely empirical and qualitative, leaving the quantitative roles of heterogeneous interaction patterns mechanistically unresolved. To address this gap, we adopt the classical SIR epidemic model to describe information spreading within mixed passenger groups, and using representative flight scenarios, we construct a dynamic network model grounded in a discrete-time Markov chain, which allows us to explicitly separate movement patterns from information propagation patterns. Through simulations, we examine how transmission intensity, interaction probability, and the parameters of the power-law contact distributions affect the ultimate information coverage and spreading speed. Results reveal that both individual-level contact heterogeneity and cross-group transmission intensity jointly determine the final coverage and spreading speed, with transmission intensity between different passenger groups exerting a particularly pronounced influence on the overall spread. Conversely, elevated transmission probabilities within the cabin crew exhibit a moderating effect on the progression of information spreading. These findings underscore the critical role of group-level transmission dynamics and offer quantitative insights for designing more effective communication strategies in aviation services.