Detecting and analyzing research communities in longitudinal scientific networks

A growing body of evidence shows that collaborative teams and communities tend to produce the highest-impact scientific work. This paper proposes a new method to (1) Identify collaborative communities in longitudinal scientific networks, and (2) Evaluate the impact of specific research institutes, s...

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Detalles Bibliográficos
Autores principales: Leone Sciabolazza, Valerio, Vacca, Raffaele, Kennelly Okraku, Therese, McCarty, Christopher
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2017
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5552257/
https://www.ncbi.nlm.nih.gov/pubmed/28797047
http://dx.doi.org/10.1371/journal.pone.0182516

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5552257/
https://www.ncbi.nlm.nih.gov/pubmed/28797047
http://dx.doi.org/10.1371/journal.pone.0182516

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