Reputation and impact in academic careers

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 C i 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 C i . 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.computational sociology | science of science | networks of networks | Matthew effect | sociophysics C itation counts are widely used to judge the impact of both scientists and their publications (1-4). Although it is recognized that many factors outside the pure merit of the research or the authors influence such counts, little effort has been devoted to identifying and quantifying the role of the author-specific factors. Recent investigations have begun to study the impact the individual scientists have through collaboration and reputation spillovers (5, 6), two integrative features of scientific careers that contribute to cumulative advantage (7-9). However, the majority of citation models avoid author-specific effects, mainly due to the difficulty in acquiring comprehensive disambiguated career data (10-13). As the measures are becoming increasingly common in evaluation scenarios throughout science, it is crucial to better understand what the citation measures actually represent in the context of scientists' careers. Moreover, how does reputation affect a scientist's access to key resources, the incentives to publish quality over quantity, and other key decisions along the career path (14-18)? In addition, what role does reputation play in the mentor-matching process within academic institutions, in the effectiveness of single/double blinding in peer review, and in the reward system of science (14,15,19)?It is against this background that we have developed a quantitative framework with the goal of isola...

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