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. 2015:2015:181038.
doi: 10.1155/2015/181038. Epub 2015 Nov 2.

Information Dissemination of Public Health Emergency on Social Networks and Intelligent Computation

Hongzhi Hu  1 , Huajuan Mao  2 , Xiaohua Hu  3 , Feng Hu  4 , Xuemin Sun  5 , Zaiping Jing  2 , Yunsuo Duan  6
Affiliations

Information Dissemination of Public Health Emergency on Social Networks and Intelligent Computation

Hongzhi Hu et al. Comput Intell Neurosci. 2015.

Abstract

Due to the extensive social influence, public health emergency has attracted great attention in today's society. The booming social network is becoming a main information dissemination platform of those events and caused high concerns in emergency management, among which a good prediction of information dissemination in social networks is necessary for estimating the event's social impacts and making a proper strategy. However, information dissemination is largely affected by complex interactive activities and group behaviors in social network; the existing methods and models are limited to achieve a satisfactory prediction result due to the open changeable social connections and uncertain information processing behaviors. ACP (artificial societies, computational experiments, and parallel execution) provides an effective way to simulate the real situation. In order to obtain better information dissemination prediction in social networks, this paper proposes an intelligent computation method under the framework of TDF (Theory-Data-Feedback) based on ACP simulation system which was successfully applied to the analysis of A (H1N1) Flu emergency.

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Figures

Figure 1
Figure 1
Participants of information dissemination in social networks.
Figure 2
Figure 2
The leading nodes and paths of information dissemination in social network.
Figure 3
Figure 3
Dynamic structure of a micro-blog network when the spreading threshold varies from 0.3 to 0.5.
Figure 4
Figure 4
ACP simulation.
Figure 5
Figure 5
TDF framework.
Figure 6
Figure 6
Relationship diagram of interconnections and strengths among websites.
Figure 7
Figure 7
Information dissemination and prediction.
See this image and copyright information in PMC

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