Research on the Dynamic Evolution Law of Online Knowledge Sharing Under Trust

Authors

  • Dan Xia Faculty of Artificial Intelligence in Education, Central China Normal University, China https://orcid.org/0000-0002-7141-8055
  • Yu Zhang Faculty of Artificial Intelligence in Education, Central China Normal University, China https://orcid.org/0009-0002-7999-4396
  • Ying Qiu Songbai Middle School of Xiamen, China
  • Si Zhang Faculty of Artificial Intelligence in Education, Central China Normal University, China
  • Yuan Tian Faculty of Artificial Intelligence in Education, Central China Normal University, China
  • Xiaoxiong Zhao Faculty of Artificial Intelligence in Education, Central China Normal University, China

DOI:

https://doi.org/10.47852/bonviewIJCE32021834

Keywords:

knowledge sharing, online learning, evolutionary game theory, Holme-Kim theoretical network model

Abstract

In the context of the COVID-19 epidemic, it has become a new trend for people to use online learning communities for learning and communication. Previous studies had shown that trust was one of the important factors affecting knowledge-sharing behavior in the online learning communities. However, related studies had not analyzed its mechanism from the micro-level. Based on the knowledge sharing gain coefficient and multi-angle trust degree of the online learning communities, this paper constructed the corresponding public goods evolution game model and constructed the Holme-Kim theoretical network model according to the structural characteristics of the community user interaction network. The simulation experiment was carried out by using Matlab to analyze the influence of group trust value and individual trust value on group sharing behavior. From the micro-level, this paper analyzed the evolution law of knowledge sharing behavior in the network under the influence of trust. The results showed that the degree of trust  knowledge sharing played an important role in improving the behavior of group knowledge sharing. This study provided theoretical guidance for improving the level of knowledge sharing in the e-learning community and creating a good learning atmosphere.

 

Received: 7 October 2023 | Revised: 15 November 2023 | Accepted: 27 November 2023

 

Conflicts of Interest

The authors declare that they have no conflicts of interest to this work.

Data Availability Statement
Data sharing is not applicable to this article as no new data were created or analyzed in this study.

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Published

2023-11-30

How to Cite

Xia, D., Zhang, Y., Qiu, Y., Zhang, S., Tian, Y., & Zhao, X. (2023). Research on the Dynamic Evolution Law of Online Knowledge Sharing Under Trust. International Journal of Changes in Education. https://doi.org/10.47852/bonviewIJCE32021834

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Research Articles

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