Evaluating the wisdom of scholar crowds from the perspective of knowledge diffusion

Le Song (), Guilong Zhu () and Xiao Yin ()
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Le Song: South China University of Technology
Guilong Zhu: South China University of Technology
Xiao Yin: South China University of Technology

Scientometrics, 2024, vol. 129, issue 9, No 3, 5103-5139

Abstract: Abstract ‘The wisdom of crowds’ theory has received widespread attention and application. For scholars, the wisdom of crowds is of great significance in revealing the operating mechanism of the scientific community. However, scholar crowds are jointly affected by scientific cognition and coordination, which are different from general human crowds. ‘The wisdom of crowds’ theory poses significant challenges in terms of directly explaining and evaluating the wisdom generation among scholars. Considering that knowledge diffusion is an important way to generate scientific cognition and coordination, this work proposed ‘the wisdom of scholar crowds’ and evaluates it from the perspective of knowledge diffusion. First, scholar-paper and scholar-topic two-layer networks were constructed, achieving a holistic representation of scientific coordination and cognition in the network structure dimension. Second, the topic consistency among scholars was identified using the two-layer networks, and a knowledge diffusion evaluation model based on topic consistency was designed to evaluate the scale and threshold of the wisdom generation of scholar crowds. Finally, combined with 3,838,048 paper data, this work revealed that the cohesion and bridging of network structure contribute to the wisdom generation of scholar crowds. By comparing with the commonly used evaluation methods, this study shows that the generating difficulty of the wisdom of scholar crowds will be underestimated without topic consistency. This work provides a new perspective for expanding the ‘wisdom of crowds’ theory and a novel method for evaluating knowledge diffusion and the wisdom of scholar crowds.

Keywords: Wisdom of crowds; Co-author network; Bibliometrics; Scientometrics; Knowledge emergence (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/s11192-024-05090-4

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