Pre-warning information dissemination models of different media under emergencies

doi:10.1088/1674-1056/ab9c0a

Abstract Pre-warning plays an important role in emergency handling, especially in urban areas with high population density like Beijing. Knowing the information dissemination mechanisms clearly could help us reduce losses and ensure the safety of human beings during emergencies. In this paper, we propose the models of pre-warning information dissemination via five classical media based on actual pre-warning issue processes, including television, radio, short message service (SMS), electronic screens, and online social networks. The population coverage ability and dissemination efficiency at different issue time of these five issue channels are analyzed by simulation methods, and their advantages and disadvantages are compared by radar graphs. Results show that SMS is the most appropriate way to issue long-term pre-warning for its large population coverage, but it is not suitable for issuing urgent warnings to large population because of the limitation of telecom company's issue ability. TV shows the best performance to combine the dissemination speed and range, and the performance of radio and electronic screens are not as satisfactory as the others. In addition, online social networks might become one of the most promising communication method for its potential in further diffusion. These models and results could help us make pre-warning issue plans and provide guidance for future construction of information diffusion systems, thus reducing injuries, deaths, and other losses under different emergencies.

Keywords: information dissemination emergency pre-warning media

Received: 01 March 2020
Revised: 11 May 2020
Accepted manuscript online: 12 June 2020

PACS:	43.10.Pr	(Information technology, internet, nonacoustical devices of interest to Acoustics)
	01.75.+m	(Science and society)
	28.41.Te	(Protection systems, safety, radiation monitoring, accidents, and dismantling)

Fund: Project supported by the Science Fund from the Ministry of Science and Technology of China (Grant No. 2018YFC0807000).

Corresponding Authors: Guofeng Su
E-mail: sugf@tsinghua.edu.cn

Cite this article:

Anying Chen(陈安滢), Haoran Zhu(朱昊然), Xiaoyong Ni(倪晓勇), Guofeng Su(苏国锋) Pre-warning information dissemination models of different media under emergencies 2020 Chin. Phys. B 29 094302

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