An evolutionary mechanism of social preference for knowledge sharing in crowdsourcing communities

IF 0.6 Q4 COMPUTER SCIENCE, THEORY & METHODS
Jianfeng Meng, Gongpeng Zhang, Zihan Li, Hongji Yang
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引用次数: 0

Abstract

Crowdsourcing community, as an important way for enterprises to obtain external public innovative knowledge in the era of the Internet and the rise of users, has a very broad application prospect and research value. However, the influence of social preference is seldom considered in the promotion of knowledge sharing in crowdsourcing communities. Therefore, on the basis of complex network evolutionary game theory and social preference theory, an evolutionary game model of knowledge sharing among crowdsourcing community users based on the characteristics of small world network structure is constructed. Through Matlab programming, the evolution and dynamic equilibrium of knowledge sharing among crowdsourcing community users on this network structure are simulated, and the experimental results without considering social preference and social preference are compared and analysed, and it is found that social preference can significantly promote the evolution of knowledge sharing in crowdsourcing communities. This research expands the research scope of the combination and application of complex network games and other disciplines, enriches the theoretical perspective of knowledge sharing research in crowdsourcing communities, and has a strong guiding significance for promoting knowledge sharing in crowdsourcing communities.
众包社区知识共享社会偏好的进化机制
众包社区作为互联网时代和用户崛起时代企业获取外部公共创新知识的重要途径,具有非常广阔的应用前景和研究价值。然而,在促进众包社区知识共享的过程中,很少考虑社会偏好的影响。因此,在复杂网络演化博弈理论和社会偏好理论的基础上,根据小世界网络结构的特点,构建了众包社区用户知识共享的演化博弈模型。通过Matlab编程,模拟了该网络结构上众包社区用户知识共享的演化过程和动态均衡,并对不考虑社会偏好和社会偏好的实验结果进行了对比分析,发现社会偏好能显著促进众包社区知识共享的演化。该研究拓展了复杂网络博弈与其他学科结合应用的研究范围,丰富了众包社区知识共享研究的理论视角,对促进众包社区知识共享具有较强的指导意义。
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来源期刊
Multiagent and Grid Systems
Multiagent and Grid Systems COMPUTER SCIENCE, THEORY & METHODS-
CiteScore
1.50
自引率
0.00%
发文量
13
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