Characterizing the Dynamics of Academic Affiliations: A Network Science Approach
Document Type
Article
Department or Administrative Unit
Mathematics
Publication Date
2-2020
Abstract
Affiliation exchanges are inherent phenomena of academia that underlies some of the structural characteristics of academic institutions. Important questions involving the dynamics of institutions’ prestige, the concentration of funding, the spread of scientific ideas, and interdisciplinarity are all related to which institution academics will move upon completion of their training, or when looking for a better environment to pursue their research endeavors. In this work, we investigated the phenomena of affiliation switches in academia and its relationship with research topics in Computer Science. Drawing from publication data spanning over thirty years, we mapped the connections among academic institutions as networks. We report on the stability of network properties over the years in spite of the exponential growth of Computer Science in recent decades. Additionally, we contextualize the structural properties of networks and topic modeling results with the current academic landscape. Altogether, our results help to characterize the phenomena of academic affiliation exchanges through the macro perspective of network science and natural language processing.
Recommended Citation
Faustino J., Iyer N., Mendonza J., Menezes R. (2020) Characterizing the Dynamics of Academic Affiliations: A Network Science Approach. In: Barbosa H., Gomez-Gardenes J., Gonçalves B., Mangioni G., Menezes R., Oliveira M. (eds.) Complex Networks XI. Springer Proceedings in Complexity. https://doi.org/10.1007/978-3-030-40943-2_33
Rights
© The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2020
Comments
This article was originally published in Complex Networks XI. The full-text article from the publisher can be found here.
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