Quantifying the evolution of individual scientific impact.

There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

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.

Related collections

Author and article information

Journal

Journal ID (iso-abbrev): Science

Title: Science (New York, N.Y.)

Publisher: American Association for the Advancement of Science (AAAS)

ISSN (Electronic): 1095-9203

ISSN (Print): 0036-8075

Publication date (Electronic): Nov 04 2016

Volume: 354

Issue: 6312

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.

Article

Publisher Item ID: 354/6312/aaf5239

DOI: 10.1126/science.aaf5239

PubMed ID: 27811240

SO-VID: 2de95529-ce16-4374-82fd-ef58f42f080e

History

Data availability:

Comments

Comment on this article

scite_

Cited by 168

See all cited by