Examining patterns of scientific knowledge diffusion based on knowledge cyber infrastructure: a multi-dimensional network approach
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Diffusion of scientific knowledge plays an important role in scientific development. Based on electronic traces of knowledge flows in knowledge cyber infrastructure, this study examines patterns of knowledge diffusion and how it is affected by the attributes of individual researchers. Methodologically, we propose a multi-dimensional network framework to examine patterns of scientific knowledge diffusion. Individual researchers are represented as nodes and knowledge flows are represented as network ties. Multiple types of nodes and ties are modeled to reflect multi-dimensionality. Exponential random graph model is employed to identify patterns of knowledge diffusion. Results show that social capital factors such as collaboration experience, credibility, and similarity in career length positively affect knowledge diffusion. Researchers’ activity level affects knowledge co-creation positively, but not knowledge transfer. Findings from this research can be used as guidance for policy makers to stimulate knowledge diffusion process more effectively. The study also contributes to the conceptualization of multi-dimensional scientific knowledge diffusion networks and provides a methodological framework that can be used to examine other general multi-dimensional networks.
KeywordsKnowledge diffusion Social network analysis Exponential random graph models Network multi-dimensionality
Funding was provided by National Science Foundation (Grant Nos. CMMI-1442116 and CMMI-1832926).
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