@inproceedings{ce5ba812ee1547e1a2f5a492bb87b5f8,
title = "Communicating hurricane risks: Multi-method examination of risk imagery diffusion",
abstract = "Conveying uncertainty in information artifacts is difficult; the challenge only grows as the demand for mass communication through multiple channels expands. In particular, as natural hazards increase with changing global conditions, including hurricanes which threaten coastal areas, we need better means of communicating uncertainty around risks that empower people to make good decisions. We examine how people share and respond to a range of visual representations of risk from authoritative sources during hurricane events. because these images are now shared widely on social media platforms, Twitter provides the means to study them on a large scale as close to in vivo as possible. Using mixed methods, this study analyzes diffusion of and reactions to forecast and other risk imagery during the highly damaging 2017 Atlantic hurricane season to describe the collective response to visual representations of risk.",
keywords = "Images, Information diffusion, Risk communication",
author = "Melissa Bica and Demuth, \{Julie L.\} and Dykes, \{James E.\} and Leysia Palen",
note = "Publisher Copyright: {\textcopyright} 2019 Copyright held by the owner/author(s).; 2019 CHI Conference on Human Factors in Computing Systems, CHI 2019 ; Conference date: 04-05-2019 Through 09-05-2019",
year = "2019",
month = may,
day = "2",
doi = "10.1145/3290605.3300545",
language = "English",
series = "Conference on Human Factors in Computing Systems - Proceedings",
publisher = "Association for Computing Machinery",
booktitle = "CHI 2019 - Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems",
address = "United States",
}