Reputation and Impact in Academic Careers

Proceedings of the National Academy of Science USA 111, 15316-15321, 2014, DOI:10.1073/pnas.1323111111

52 Pages Posted: 22 Nov 2014 Last revised: 17 Jun 2016

See all articles by Alexander Michael Petersen

Alexander Michael Petersen

University of California Merced, Ernest and Julio Gallo Management Program

Santo Fortunato

Aalto University

Raj Pan

Aalto University

Kimmo Kaski

Aalto University

Orion B. Penner

Ecole Polytechnique Fédérale de Lausanne

Armando Rungi

IMT School for Advanced Studies Lucca, AXES Lab

Massimo Riccaboni

KU Leuven - Department of Managerial Economics, Strategy, and Innovation; IMT Institute for Advanced Studies

H. Eugene Stanley

Boston University - Center for Polymer Studies

Fabio Pammolli

Polytechnic University of Milan - Department of Management, Economics and Industrial Engineering; CERM Foundation

Date Written: October 8, 2014

Abstract

Reputation is an important social construct in science, which enables informed quality assessments of both publications and careers of scientists in the absence of complete systemic information. However, the relation between reputation and career growth of an individual remains poorly understood, despite recent proliferation of quantitative research evaluation methods. Here we develop an original framework for measuring how a publication's citation rate Δc depends on the reputation of its central author i, in addition to its net citation count c. To estimate the strength of the reputation effect, we perform a longitudinal analysis on the careers of 450 highly-cited scientists, using the total citations Ci of each scientist as his/her reputation measure. We find a citation crossover cx which distinguishes the strength of the reputation effect. For publications with cx, the author's reputation is found to dominate the annual citation rate. Hence, a new publication may gain a significant early advantage corresponding to roughly a 66% increase in the citation rate for each tenfold increase in Ci. However, the reputation effect becomes negligible for highly cited publications meaning that for c > cx the citation rate measures scientific impact more transparently. In addition we have developed a stochastic reputation model, which is found to reproduce numerous statistical observations for real careers, thus providing insight into the microscopic mechanisms underlying cumulative advantage in science.

Keywords: computational sociology, science of science, networks of networks, Matthew effect, cumulative advantage, citations, careers

Suggested Citation

Petersen, Alexander Michael and Fortunato, Santo and Pan, Raj and Kaski, Kimmo and Penner, Orion B. and Rungi, Armando and Riccaboni, Massimo and Stanley, H. Eugene and Pammolli, Fabio, Reputation and Impact in Academic Careers (October 8, 2014). Proceedings of the National Academy of Science USA 111, 15316-15321, 2014, DOI:10.1073/pnas.1323111111, Available at SSRN: https://ssrn.com/abstract=2528779

Alexander Michael Petersen (Contact Author)

University of California Merced, Ernest and Julio Gallo Management Program ( email )

School of Engineering
Science & Engineering 2, Suite 315
Merced, CA 95343
United States

Santo Fortunato

Aalto University ( email )

P.O. Box 21210
Helsinki, 00101
Finland

Raj Pan

Aalto University ( email )

P.O. Box 21210
Helsinki, 00101
Finland

Kimmo Kaski

Aalto University ( email )

P.O. Box 21210
Helsinki, 00101
Finland

Orion B. Penner

Ecole Polytechnique Fédérale de Lausanne ( email )

Station 5
Odyssea 1.04
1015 Lausanne, CH-1015
Switzerland

Armando Rungi

IMT School for Advanced Studies Lucca, AXES Lab ( email )

Piazza S. Francesco 19
Lucca, IT-55100
Italy

Massimo Riccaboni

KU Leuven - Department of Managerial Economics, Strategy, and Innovation ( email )

Naamsestraat 69 bus 3500
Leuven, 3000
Belgium

IMT Institute for Advanced Studies ( email )

Complesso San Micheletto
Lucca, 55100
Italy

H. Eugene Stanley

Boston University - Center for Polymer Studies ( email )

Boston, MA 02215
United States

Fabio Pammolli

Polytechnic University of Milan - Department of Management, Economics and Industrial Engineering ( email )

Via Lambruschini 4C - building 26/A
Milano, 20156
Italy

CERM Foundation ( email )

Via Fiorentina, 1
Siena, Siena 53100
Italy

HOME PAGE: http://www.cermlab.it

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