Understanding the advisor–advisee relationship via scholarly data analysis
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Advisor–advisee relationship is important in academic networks due to its universality and necessity. Despite the increasing desire to analyze the career of newcomers, however, the outcomes of different collaboration patterns between advisors and advisees remain unknown. The purpose of this paper is to find out the correlation between advisors’ academic characteristics and advisees’ academic performance in Computer Science. Employing both quantitative and qualitative analysis, we find that with the increase of advisors’ academic age, advisees’ performance experiences an initial growth, follows a sustaining stage, and finally ends up with a declining trend. We also discover the phenomenon that accomplished advisors can bring up skilled advisees. We explore the conclusion from two aspects: (1) Advisees mentored by advisors with high academic level have better academic performance than the rest; (2) Advisors with high academic level can raise their advisees’ h-index ranking. This work provides new insights on promoting our understanding of the relationship between advisors’ academic characteristics and advisees’ performance, as well as on advisor choosing.
KeywordsAcademic networks Scholarly data Social network analysis Advisor–advisee relationship Collaboration patterns
The authors extend their appreciation to the Deanship of Scientific Research at King Saud University for funding this work through research group NO (RG-1438-027). Xiangjie Kong is supported by Fundamental Research Funds for the Central Universities under Grant NO (DUT18JC09), and China Scholarship Council under Grant NO (201706060067).
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