Future impact: Predicting scientific success

See on Scoop.itBizDissNews; Showcasing recent PhD dissertations in Business Research

Abstract: To construct a formula to predict future h-index, we assembled a large data set and analysed it using machine-learning techniques. Our initial sample from academictree.org — a crowd-sourced website listing scientists’ mentors, trainees and collaborators — contains the names and institutions of about 34,800 neuroscientists, 2,000 scientists studying the fruitfly Drosophila and 1,300 evolutionary researchers. We matched these authors to records in Scopus, an online database of academic papers and citation data. We restricted our analysis to authors who had accrued an h-index greater than 4 (to exclude inactive scientists); to publications after 1995 (because electronic records are sparse before then); to authors who had published their first manuscript in the past 5–12 years; and to authors who were identifiable in Scopus.

 

Future impact: Predicting scientific success

Daniel E. Acuna, Stefano Allesina & Konrad P. Kording

Nature 489, 201–202 (13 September 2012) http://dx.doi.org/10.1038/489201a

 

Supplementary material:

http://www.nature.com/nature/journal/v489/n7415/extref/489201a-s1.pdf

 

See on www.nature.com

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About Wilfred Mijnhardt
RMIMR is my virtual playground, a place to reflect on issues from my professional context, my job as Policy Director at Rotterdam School of Management, Erasmus University (RSM). RSM is the international university based business school at Erasmus University Rotterdam. More info here: www.rsm.nl Here is my list of relevant publications on the topic of my RMIMR weblog: http://www.mendeley.com/collections/694621/RMIMR-Repository/ The rss feed for my RMIMR collection is here: http://www.mendeley.com/collections/rss/694621/ Here is my other weblog on impact of research: http://www.scoop.it/t/dualimpact

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