Citation

Sadri AM, Ukkusuri SV, Ahmed MA. Transp. Res. Interdiscip. Persp. 2021; 9: e100325.

Copyright

(Copyright © 2021, Elsevier Publishing)

DOI

10.1016/j.trip.2021.100325

PMID

unavailable

Abstract

Topography and dynamics of real networks' enable network agents to alter their functional behavior. Theoretical and analytical advancements in network science have furthered our understanding of the effects of social network characteristics on peer influence and engagement. Influence of social network occurs when network players alter their decisions and behavior based on others' influence in the social network which is evident in different disciplines. Crisis communication networks have significant impact during disasters as people often spread pertinent information in social media due to presence of limited access to conventional information sources. Existing researches in social science and sociology indicate that social networks benefit spreading warning message and disseminate information about an imminent risk, nevertheless, the existing studies do not provide enough understanding on how to quantify such influences and how this map into decision-making during emergency evacuations. This study provides a robust review of the studies exploring how individuals are socially influenced, both on-line and off-line, while communicating risk during extreme weather events such as hurricanes. The scope of this review primarily includes studies that look into how our social networks influence the way we decide to evacuate and how crisis information spread from one agent to another agent in a network. The insights and findings obtained through this comprehensive review will be useful to diverse set of stakeholders such as emergency managers, planners, policy makers and practitioners. These include identifying and implementing targeted strategies for different groups of people in similar crisis events based on their social network properties, interactions, and activities.

Language: en

Keywords

Crisis communications; Decision making; Evacuation modeling; Resilience; Social influence; Social networks