Abstract
Science can be examined from several standpoints, such as through a bibliometric analysis of the scientific output of researchers, research groups or institutions. However, there is little information about the advisor–advisee relationships or the academic supervision of researchers or between teachers and students. In this paper, we examine the results of the academic genealogy of PhD and Master’s students working in Brazil, which was obtained from 737,919 curriculum vitae extracted from the Lattes Platform. Our findings bring to light three main sources of evidence related to the Brazilian academic genealogy: (1) the degree of interdisciplinarity between main areas of knowledge, (2) the structural features and evolving patterns with regard to both areas of knowledge and researchers, and (3) the patterns in the levels of training that affect the topological metrics. We conclude that academic genealogy offers a great opportunity to assess researchers and their areas of research from the perspective of human resource training.
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The authors would like to thank the Federal University of ABC for its financial support.
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Appendix
We investigated the influence between main areas of knowledge in both PhD and MSc & PhD graphs. Figure 9 shows 16 radar charts (two by main area of knowledge). The axis of the radar charts uses the logarithmic function applied to the data shown in Table 4. As observed in Table 4, main areas of knowledge have a certain degree of interdisciplinarity. Moreover, while comparing the two graphs, there is a similar pattern in the influence exerted and experienced for both graphs PhD and MSc & PhD.
We also analyzed who are the fifteen artificial nodes with the highest values for each of the five metrics. Table 7 presents the values for the metrics descendants and fecundity, as well as the genealogical index for the 15 researchers without Lattes ID with the highest values, for both PhD and MSc & PhD graphs.
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Damaceno, R.J.P., Rossi, L., Mugnaini, R. et al. The Brazilian academic genealogy: evidence of advisor–advisee relationships through quantitative analysis. Scientometrics 119, 303–333 (2019). https://doi.org/10.1007/s11192-019-03023-0
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DOI: https://doi.org/10.1007/s11192-019-03023-0