Communicating Hurricane Risks: Multi-Method Examination of Risk Imagery Diffusion

被引:24
作者
Bica, Melissa [1 ]
Demuth, Julie L. [2 ]
Dykes, James E. [1 ]
Palen, Leysia [1 ]
机构
[1] Univ Colorado, Boulder, CO 80309 USA
[2] Natl Ctr Atmospher Res, POB 3000, Boulder, CO 80307 USA
来源
CHI 2019: PROCEEDINGS OF THE 2019 CHI CONFERENCE ON HUMAN FACTORS IN COMPUTING SYSTEMS | 2019年
基金
美国国家科学基金会;
关键词
Images; Information Diffusion; Risk Communication; FORECAST UNCERTAINTY; WEATHER FORECASTS; PERCEPTION; TWITTER; MODEL;
D O I
10.1145/3290605.3300545
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
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.
引用
收藏
页数:13
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