| Content Provider |
World Health Organization (WHO)-Global Index Medicus |
| Author |
Penner, Orion Pammolli, Fabio Kaski, Kimmo Petersen, Alexander Michael Pan, Raj K. Rungi, Armando Fortunato, Santo Stanley, H. Eugene Riccaboni, Massimo |
| Description |
Author Affiliation: Petersen AM ( Laboratory for the Analysis of Complex Economic Systems, Institutions, Markets, Technologies (IMT) Lucca Institute for Advanced Studies, 55100 Lucca, Italy); Fortunato S ( Department of Biomedical Engineering and Computational Science, Aalto University School of Science, FI-00076 Aalto, Finland); Pan RK ( Department of Biomedical Engineering and Computational Science, Aalto University School of Science, FI-00076 Aalto, Finland); Kaski K ( Department of Biomedical Engineering and Computational Science, Aalto University School of Science, FI-00076 Aalto, Finland); Penner O ( Laboratory of Innovation Management and Economics, IMT Lucca Institute for Advanced Studies, 55100 Lucca, Italy); Rungi A ( Laboratory for the Analysis of Complex Economic Systems, Institutions, Markets, Technologies (IMT) Lucca Institute for Advanced Studies, 55100 Lucca, Italy); Riccaboni M ( Laboratory of Innovation Management and Economics, IMT Lucca Institute for Advanced Studies, 55100 Lucca, Italy); Stanley HE ( Center for Polymer Studies and Department of Physics, Boston University, Boston, MA 02215 hes@bu.edu petersen.xander@gmail.com santo.fortunato@aalto.fi.); Pammolli F ( Laboratory for the Analysis of Complex Economic Systems, Institutions, Markets, Technologies (IMT) Lucca Institute for Advanced Studies, 55100 Lucca, Italy); |
| 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 c×, which distinguishes the strength of the reputation effect. For publications with c < c×, 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 ≥ c×, 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. |
| ISSN |
00278424 |
| e-ISSN |
10916490 |
| Journal |
Proceedings of the National Academy of Sciences of the United States of America |
| Issue Number |
43 |
| Volume Number |
111 |
| Language |
English |
| Publisher |
National Academy of Sciences |
| Publisher Date |
2014-10-01 |
| Publisher Place |
United States |
| Access Restriction |
Open |
| Subject Keyword |
Bibliometrics Career Mobility Statistics & Numerical Data Research Personnel Research Computer Simulation Models, Statistical Monte Carlo Method Research Support, Non-U.S. Gov't Research Support, U.S. Gov't, Non-P.H.S. Multidisciplinary |
| Content Type |
Text |
| Resource Type |
Article |
| Subject |
Multidisciplinary |
