Topological metrics in academic genealogy graphs
Rafael J.P. Damaceno,
Igor L. Freire,
Etelvino J.H. Bechara and
Mena-Chalco, Jesús P.
Journal of Informetrics, 2018, vol. 12, issue 4, 1042-1058
Academic genealogy aims to structure and analyze the mentoring relationships between advisor and advisee. The representation of this structure results in academic genealogy graphs. For the analysis and characterization of these graphs, we present a set of metrics and their corresponding mirror metrics that capture the characteristics of its topological structure and represent them as quantitative attributes. The metrics of fecundity, fertility, descendants, cousins, generations, and relationships consider the descendants of the academics represented in the graph. The mirror metric of these topological metrics considers the ascendancy of academics. Individually, the metrics have strong semantic intuition and define characteristics regarding the performance in the mentoring of an academic. Together, the metrics are useful for the identification, characterization, and classification of communities and their members. The genealogical data available through the platforms of the Mathematics Genealogy Project and the Academic Family Tree were used as case studies. Two hundred thirteen thousand and 675,000 academic records were obtained for each project. We analyze the capacity of characterization of the metrics using the structuring of a similarity graph and through the distribution of the nodes in principal components. We observed that the set of metrics is capable of capturing the configuration pattern existing in genealogy graphs independently of its scale.
Keywords: Topological metrics; Academic genealogy; Advisor–advisee relationship; Genealogical graph (search for similar items in EconPapers)
References: View references in EconPapers View complete reference list from CitEc
Citations Track citations by RSS feed
Downloads: (external link)
Full text for ScienceDirect subscribers only
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:eee:infome:v:12:y:2018:i:4:p:1042-1058
Access Statistics for this article
Journal of Informetrics is currently edited by Leo Egghe
More articles in Journal of Informetrics from Elsevier
Bibliographic data for series maintained by Dana Niculescu ().