Understanding how to accurately inform the population about the risks of disasters is key for the well-functioning ofour societies. Risk communication is also an essential feature of the disaster cycle, fundamentally contributing topreparedness but also to management. Here, we use an agent-based model (ABM) to investigate such an importantproblem. Specifically, we study the emergent behavior of a population of individuals who revise their opinion on therisk of a certain event, based on information received from an institution, processed through individual sensitivity,and discussed with peers. Such a complex process may include several biases, e.g., due to heterogeneous riskperception across the population, and homophily, i.e., tendency of individuals to interact with like-minded people.Our ABM, which encapsulates these crucial features, allows us to perform a campaign of numerical simulationstowards gaining mathematically-grounded insights into their impact on the emergent behavior of the population and,ultimately, on how accurately institutional information is received and processed by a population. Such insightscan be useful to design empirical studies to test them and, in case of empirical support, to use them to designrecommendations for policy decision makers.

Homophily in opinion networks affects collective risk perception in heterogeneous populations / Giardini, Francesca; Vilone, Daniele; Zino, Lorenzo; Cao, Ming. - ELETTRONICO. - 21:(2024). (Intervento presentato al convegno ISCRAM 2024 tenutosi a Münster (Germania) nel 25-29 May, 2024).

Homophily in opinion networks affects collective risk perception in heterogeneous populations

Lorenzo Zino;
2024

Abstract

Understanding how to accurately inform the population about the risks of disasters is key for the well-functioning ofour societies. Risk communication is also an essential feature of the disaster cycle, fundamentally contributing topreparedness but also to management. Here, we use an agent-based model (ABM) to investigate such an importantproblem. Specifically, we study the emergent behavior of a population of individuals who revise their opinion on therisk of a certain event, based on information received from an institution, processed through individual sensitivity,and discussed with peers. Such a complex process may include several biases, e.g., due to heterogeneous riskperception across the population, and homophily, i.e., tendency of individuals to interact with like-minded people.Our ABM, which encapsulates these crucial features, allows us to perform a campaign of numerical simulationstowards gaining mathematically-grounded insights into their impact on the emergent behavior of the population and,ultimately, on how accurately institutional information is received and processed by a population. Such insightscan be useful to design empirical studies to test them and, in case of empirical support, to use them to designrecommendations for policy decision makers.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/2989334