Paper Info
Title
Information dissemination of public health emergency on social networks and intelligent computation
Abstract
AbstractDue 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.
Year
DOI
Venue
2015
10.1155/2015/181038
Periodicals
Field
DocType
Volume
Social network,Computer science,Computer security,Risk analysis (engineering),Social influence,Emergency medical services,Artificial intelligence,Social support,Public health,Information processing,Emergency management,Information Dissemination,Machine learning
Journal
2015
Issue
ISSN
Citations 
1
1687-5265
0
PageRank 
References 
Authors
0.34
6
7
Name
Order
Citations
PageRank
Hongzhi Hu1141.82
Huajuan Mao200.68
Xiaohua Hu32819314.15
Feng Hu470.89
Xuemin Sun570.89
Zaiping Jing600.34
Yunsuo Duan700.68