Modeling study of knowledge diffusion in scientific collaboration networks based on differential dynamics: A case study in graphene field

knowledge diffusion based on scientific collaboration is similar to disease propagation through actual contact. Inspired by the disease-spreading model in complex networks, this study classifies the states of research entities during the process of knowledge diffusion in scientific collaboration into four categories. Research entities can transform from one state to another with a certain probability, which results in the evolution rules of knowledge diffusion in scientific collaboration networks. The knowledge diffusion model of differential dynamics in scientific collaboration of non-uniformity networks is formed, and the relationship between the degree distribution and evolution of knowledge diffusion is further discussed, to reveal the dynamic mechanics of knowledge diffusion in scientific collaboration networks. Finally, an empirical analysis is conducted on knowledge diffusion in an institutional scientific collaboration network by taking the graphene field as an example. The results show that the state evolution of research entities in the knowledge diffusion process of scientific collaboration networks is affected not only by the evolution states of adjacent research entities with whom they have certain collaboration relationships, but also by the structural attributes and degree distributions of scientific collaboration networks. The evolution of knowledge diffusion in scientific collaboration entities with different degrees also shows different trends.

https://doi.org/10.1016/j.physa.2019.04.201

Author(s):Zenghui Yue, Haiyun Xu, Guoting Yuan, Hongshen Pang
Organization(s):Jining Medical University, Chengdu Documentation and Information Center, Chinese Academy of Sciences
Source: Physica A: Statistical Mechanics and its Applications
Year: 2019

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