Networked risk perception and behavioral bubbles: the case of a pandemic

2026-06-21

AI Summary

This study addresses a critical limitation in traditional risk perception models, which often overlook social interactions and thus fail to explain the localized clustering and bounded diffusion of behavioral responses during crises. Leveraging weekly mobility data from 313 municipalities in Massachusetts during the early pandemic phase and pre-pandemic inter-municipal travel networks, the authors employ a two-way fixed-effects panel regression to disentangle local case-driven reactions, cross-municipal behavioral spillovers, and within-municipality behavioral inertia. The analysis provides the first empirical evidence that behavioral spillovers are strictly confined within communities defined by mobility networks and are significant only between connected municipalities with similar population sizes. Moreover, peer behavior emerges as a stronger driver of risk perception than local case counts. These findings challenge assumptions of administrative-boundary-based risk responses and reveal risk perception as an inherently networked and normative social process.

Abstract

Risk perception is typically modeled as an individual cognitive readout of objective hazard, yet during crises what people judge as risky is shaped by what their peers do. Using weekly mobility data from 313 Massachusetts municipalities over the first year of the COVID-19 pandemic and a pre-pandemic inter-town mobility network that fixes interaction structure before the shock, we estimate two-way fixed-effects panel regressions that separate local case response, inter-town behavioral spillover along the mobility network, and within-town inertia; the pre-shock network and a lagged peer signal address the standard reflection and endogenous-group concerns. Three findings emerge. First, inter-town behavioral spillovers are substantial and localize almost entirely within mobility-defined communities, with effectively no propagation across community boundaries, the empirical referent of behavioral bubbles. Second, the within-community spillover carries behavioral content beyond peer-town case information: when network-exposure-to-cases and network-exposure-to-behavior are raced, the behavioral channel survives and the case-exposure channel goes null. Third, a joint mobility-by-demographic decomposition shows the spillover requires both routine connection and demographic similarity. It concentrates where towns are connected and similar, and vanishes between similar towns that are not connected, ruling out a shared-conditions confound and pointing to an observational and normative channel rather than a purely informational one. These results recast risk perception as a networked phenomenon and identify mobility-defined communities, rather than administrative units, as the operative scale of behavioral response. The pattern should generalize wherever exposure is uncertain, evolving, and socially negotiated, including climate adaptation and financial contagion.

Problem

• risk perception
• behavioral spillover
• mobility network
• behavioral bubbles
• social influence

Innovation

• networked risk perception
• behavioral spillovers
• mobility-defined communities
• behavioral bubbles
• two-way fixed-effects panel regression