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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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| Publicado no: | PLoS One |
|---|---|
| Main Authors: | , , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
Public Library of Science
2017
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC5552257/ https://ncbi.nlm.nih.gov/pubmed/28797047 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1371/journal.pone.0182516 |
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