Literature DB >> 27811240

Quantifying the evolution of individual scientific impact.

Roberta Sinatra1,2, Dashun Wang3,4, Pierre Deville1,5, Chaoming Song6, Albert-László Barabási7,8,9,10.   

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.
Copyright © 2016, American Association for the Advancement of Science.

Year:  2016        PMID: 27811240     DOI: 10.1126/science.aaf5239

Source DB:  PubMed          Journal:  Science        ISSN: 0036-8075            Impact factor:   47.728


  61 in total

1.  Modeling research universities: Predicting probable futures of public vs. private and large vs. small research universities.

Authors:  William B Rouse; John V Lombardi; Diane D Craig
Journal:  Proc Natl Acad Sci U S A       Date:  2018-12-11       Impact factor: 11.205

2.  Changing demographics of scientific careers: The rise of the temporary workforce.

Authors:  Staša Milojević; Filippo Radicchi; John P Walsh
Journal:  Proc Natl Acad Sci U S A       Date:  2018-12-11       Impact factor: 11.205

3.  History of art paintings through the lens of entropy and complexity.

Authors:  Higor Y D Sigaki; Matjaž Perc; Haroldo V Ribeiro
Journal:  Proc Natl Acad Sci U S A       Date:  2018-08-27       Impact factor: 11.205

4.  Improving data access democratizes and diversifies science.

Authors:  Abhishek Nagaraj; Esther Shears; Mathijs de Vaan
Journal:  Proc Natl Acad Sci U S A       Date:  2020-09-08       Impact factor: 11.205

5.  The misleading narrative of the canonical faculty productivity trajectory.

Authors:  Samuel F Way; Allison C Morgan; Aaron Clauset; Daniel B Larremore
Journal:  Proc Natl Acad Sci U S A       Date:  2017-10-17       Impact factor: 11.205

6.  Opinion: The Next Generation Researchers Initiative at NIH.

Authors:  Michael Lauer; Lawrence Tabak; Francis Collins
Journal:  Proc Natl Acad Sci U S A       Date:  2017-11-07       Impact factor: 11.205

7.  The Matthew effect in science funding.

Authors:  Thijs Bol; Mathijs de Vaan; Arnout van de Rijt
Journal:  Proc Natl Acad Sci U S A       Date:  2018-04-23       Impact factor: 11.205

8.  Quantifying the future lethality of terror organizations.

Authors:  Yang Yang; Adam R Pah; Brian Uzzi
Journal:  Proc Natl Acad Sci U S A       Date:  2019-10-07       Impact factor: 11.205

9.  Scientific elite revisited: patterns of productivity, collaboration, authorship and impact.

Authors:  Jichao Li; Yian Yin; Santo Fortunato; Dashun Wang
Journal:  J R Soc Interface       Date:  2020-04-22       Impact factor: 4.118

10.  Intellectual synthesis in mentorship determines success in academic careers.

Authors:  Jean F Liénard; Titipat Achakulvisut; Daniel E Acuna; Stephen V David
Journal:  Nat Commun       Date:  2018-11-27       Impact factor: 14.919

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