Abstract
By collecting the publication data of scientists belonging to China’s Project 985 universities in the chemistry field and classifying the scientists into Distinguished Young Scholars (DYSs) and non-Distinguished Young Scholars (non-DYSs), this study constructed scientists’ ego research collaboration networks and compared the network differences between DYSs and non-DYSs, who usually occupy different structural positions in the science community. We employed three network indicators (degree centrality, betweenness centrality and tie strength) to measure the advantages related to network locations. Then, we investigated and compared DYSs’ and non-DYSs’ capability of using the social capital embedded in their research collaboration networks to improve their research performance. The results show that DYSs exhibit the better capability to use social capital from research collaboration networks and that their Ph.D. mentors may be a critical factor in scientific success. We further discussed the theoretical and practical implications at the end of this study.
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Data availability
The publication data used in this manuscript were extracted from Web of Science Core Collection. Personal data were collected in scientists’ website, Baidu and Google engines.
Code availability
The network indicators were calculated by using MATLAB 2016b, and Regression analysis were conducted by Stata 15.0.
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Funding
This work was supported by National Natural Science Foundation of China [71810107004; L1924081; 71573017; 71872169], University of Chinese Academy of Sciences, Fundamental Research Funds for the Central Universities [E1E42107]. The funding organizations have played no role in the conduct of this study.
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Conceptualization: YL; Methodology, formal analysis and investigation: YL; Writing-original draft preparation: MZ; Writing-review and editing: GZ; Funding acquisition: YL and GZ; Data collection and supervision: XY.
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Liu, Y., Zhang, M., Zhang, G. et al. Scientific elites versus other scientists: who are better at taking advantage of the research collaboration network?. Scientometrics 127, 3145–3166 (2022). https://doi.org/10.1007/s11192-022-04362-1
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DOI: https://doi.org/10.1007/s11192-022-04362-1