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New Technology of Library and Information Service  2016, Vol. 32 Issue (7-8): 32-41    DOI: 10.11925/infotech.1003-3513.2016.07.05
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A BDI-Agent Based Model for Public Opinion Crisis Response
Wu Peng1,2,3(),Jin Beibei1,2,3,Qiang Shaohua4
1School of Economics and Management, Nanjing University of Science &Technology, Nanjing 210094, China
2Jiangsu Collaborative Innovation Center of Social Safety Science and Technology, Nanjing 210094, China
3Hubei Collaborative Innovation Center for Early Warning and Emergency Response Technology, Wuhan 430070, China
4School of Economics and Management, Nanjing University of Technology, Nanjing 211800, China
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[Objective] This paper analyzes the motivation and evolution of netizens’ behavior in crises with the help of the “Belief-Desire-Intention (BDI)” model to guide netizens’ emotion, and then builds a computing model for crisis response in the complex network environment. [Methods] First, we designed a model for interaction among netizens, government and media in public opinion crisis to simulate the netizens’ emotional changes, based on the BDI-Agent theoretical model. This model could reveal reasons for the changing of public opinion and help us create better crisis response strategies. Second, we built an experimental model with the Agent property, reasoning rules and interaction designs to examine the algorithm with real world cases. [Results] Our empirical study showed that the proposed model was feasible. [Limitations] More real world cases were needed to further optimize the new model. [Conclusions] The proposed BDI-agent model could map the complicated public opinion context to a reasonable computing model, which could help us predict the future development of the public opinion crises and design better response strategy.

Key wordsEmergency affairs      Public opinion      Crisis response      Belief-Desire-Intention model     
Received: 12 June 2016      Published: 29 September 2016

Cite this article:

Wu Peng,Jin Beibei,Qiang Shaohua. A BDI-Agent Based Model for Public Opinion Crisis Response. New Technology of Library and Information Service, 2016, 32(7-8): 32-41.

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