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Simulating Public Opinion Evolution with Scale-Free Network Model and Infectious Disease Model |
Han Pu1,2(), Wang Peng1 |
1 School of Management, Nanjing University of Posts & Telecommunications, Nanjing 210003, China 2 Jiangsu Key Laboratory of Data Engineering and Knowledge Service, Nanjing 210023, China |
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Abstract [Objective] This article tries to explore the information dissemination status and process in the social network systems, aiming to reveal the online information evolution mechanism. [Methods] First, we added adjustable parameters to the scale-free network model and the infectious disease model. Then, we executed the modified model on the NetLogo platform to simulate the evolution of public opinion. [Results] We found that the changing propagation rate was a better way to describe the online information dissemination process. We could effectively guide and control the information flow in a large network at the stage with increasing propagation rate. [Limitations] We need better classification method for the target population. [Conclusions] The proposed model could simulate information evolution and then support the online public opinion monitoring, guidance and control.
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Received: 31 May 2017
Published: 08 November 2017
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