Smart Evolution for Information Diffusion Over Social Networks
| Autor: | Yuejiang Li, H. Vicky Zhao, Yan Chen, Hangjing Zhang |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
021110 strategic
defence & security studies Social network Computer Networks and Communications Process (engineering) business.industry Computer science media_common.quotation_subject 0211 other engineering and technologies Evolutionary game theory 02 engineering and technology Computer security computer.software_genre Reciprocity (evolution) Incentive Order (exchange) Norm (social) Safety Risk Reliability and Quality Evolutionary dynamics business computer Game theory Reputation media_common |
| Zdroj: | IEEE Transactions on Information Forensics and Security. 16:1203-1217 |
| ISSN: | 1556-6021 1556-6013 |
| DOI: | 10.1109/tifs.2020.3032039 |
| Popis: | In social network, the existence of malicious users can create lots of detrimental consequences. To diminish their negative influences, it is necessary for rational users to identify and interact with each neighbor carefully to protect themselves from malicious ones. Therefore, it is crucial to establish a rule for users’ interaction in order to mitigate malicious users’ influences. In this paper, we propose a smart evolution model based on evolutionary game theory by introducing the reputation mechanism. The model takes into account both current reputation and instant incentives during users’ decision-making process. On the basis of whether users share reputation values with others, we introduce schemes without reciprocity principle and with the indirect reciprocity principle respectively. With the social norm and reputation updating policy, we theoretically analyze the evolutionary dynamics and corresponding ESSs by explicitly considering the effects of malicious users. Finally, simulations based on synthetic networks and real-world data are conducted to validate the effectiveness of the proposed smart evolution model. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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