Synergistic cellular automata model for dissemination of Internet public opinion
FANG Wei1,HE Liu-jin2,SONG Liang-tu1
1. Institute of Intelligent Machines, Chinese Academy of Sciences, Hefei Anhui 230031, China 2. Huainan Office of Information Application, Anhui Province, Huainan Anhui 232000, China
Abstract：As for the present research on the dissemination of Internet Public Opinion (IPO), some research use mathematic statistics or intelligent learning to analyze the growing or descending process of a topic related text, and some use cellular automata or Hidden Markov Model (HMM) to find the tendency propagation of the subject of IPO. However, all of them lack the analyses of the impacts of the subject attributes in IPO on its tendency propagation. Based on the systematic synergy of IPO space, the synergistic transition probability between states on whole cells space of discussed IPO was computed firstly, and then it was compared with a local state probability in 9 neighbors of a central cell to decide whether the state of central cell should be converted. After several iterative operations, the degree (magnetisability) which expressed the tendency propagation upon to "+" or "-" was obtained. Through observing the magnetisability-time variable curve, one can clearly handle its evolution. Therefore, a new model and an algorithm of extensive synergistic cellular automata model were presented. The simulation results show that the order-variable parameters of society adaptability can express the subject's group psychology, and it goes towards the majority opinion. Similarly, the order-variable parameters of preference fast make tendency propagation close to the direction of preference, i.e "+" or "-". The model is relatively closer to the real situation of dissemination of IPO.
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2012, Vol. 32 
