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| Information Propagation Model in Bloackchain Social Network |
| ZHAO Yan, BIN Sheng, SUN Gengxin
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| College of Computer Science & Technology, Qingdao University, Qingdao 266071, China |
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Abstract Aiming at the problem that the traditional propagation model is difficult to accurately describe the law of information propagation in the blockchain social network, based on the information propagation characteristics of blockchain social networks, this paper considers the influence of the incentive mechanism of blockchain social networks on information propagation, uses evolutionary games to define the state transition probability and proposes a new blockchain social network information propagation model. The influence of group density, state transition probability, and incentive policies on information propagation is analyzed through simulation experiments. Experimental results show that the model can accurately describe the law of information propagation in blockchain social networks. The model proposed in this paper can effectively restrain the propagation of low-quality information in social networks and further build a good network public opinion environment.
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Received: 30 March 2021
Published: 23 May 2022
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