| Literature DB >> 29496846 |
Santo Fortunato1,2, Carl T Bergstrom3, Katy Börner2,4, James A Evans5, Dirk Helbing6, Staša Milojević7, Alexander M Petersen8, Filippo Radicchi7, Roberta Sinatra9,10,11, Brian Uzzi12,13, Alessandro Vespignani11,14,15, Ludo Waltman16, Dashun Wang12,13, Albert-László Barabási17,11,18.
Abstract
Identifying fundamental drivers of science and developing predictive models to capture its evolution are instrumental for the design of policies that can improve the scientific enterprise-for example, through enhanced career paths for scientists, better performance evaluation for organizations hosting research, discovery of novel effective funding vehicles, and even identification of promising regions along the scientific frontier. The science of science uses large-scale data on the production of science to search for universal and domain-specific patterns. Here, we review recent developments in this transdisciplinary field.Entities:
Year: 2018 PMID: 29496846 PMCID: PMC5949209 DOI: 10.1126/science.aao0185
Source DB: PubMed Journal: Science ISSN: 0036-8075 Impact factor: 47.728