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
Via Complexity Digest