Quantifying the evolution of individual scientific impact

Roberta Sinatra; Dashun Wang; Pierre Deville; Chaoming Song; Albert-László Barabási

doi:10.1126/science.aaf5239

Quantifying the evolution of individual scientific impact

Science. 2016 Nov 4;354(6312):aaf5239. doi: 10.1126/science.aaf5239.

Authors

Roberta Sinatra^{1

2}, Dashun Wang^{3

4}, Pierre Deville^{1

5}, Chaoming Song⁶, Albert-László Barabási^{7

8

9

10}

Affiliations

¹ Center for Complex Network Research and Physics Department, Northeastern University, Boston, MA 02115, USA.
² Center for Network Science and Math Department, Central European University, Budapest, Hungary.
³ Kellogg School of Management, Northwestern University, Evanston, IL 60208, USA.
⁴ Northwestern Institute on Complex Systems, Northwestern University, Evanston, IL 60208, USA.
⁵ Department of Applied Mathematics, Université catholique de Louvain, Louvain-la-Neuve, Belgium.
⁶ Department of Physics, University of Miami, Coral Gables, FL 33124, USA.
⁷ Center for Complex Network Research and Physics Department, Northeastern University, Boston, MA 02115, USA. alb@neu.edu.
⁸ Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA.
⁹ Center for Network Science, Central European University, Budapest, Hungary.
¹⁰ Center for Cancer Systems Biology, Dana-Farber Cancer Institute, Boston, MA 02115, USA.

PMID: 27811240
DOI: 10.1126/science.aaf5239

Abstract

Despite the frequent use of numerous quantitative indicators to gauge the professional impact of a scientist, little is known about how scientific impact emerges and evolves in time. Here, we quantify the changes in impact and productivity throughout a career in science, finding that impact, as measured by influential publications, is distributed randomly within a scientist's sequence of publications. This random-impact rule allows us to formulate a stochastic model that uncouples the effects of productivity, individual ability, and luck and unveils the existence of universal patterns governing the emergence of scientific success. The model assigns a unique individual parameter Q to each scientist, which is stable during a career, and it accurately predicts the evolution of a scientist's impact, from the h-index to cumulative citations, and independent recognitions, such as prizes.

Publication types

Research Support, Non-U.S. Gov't