  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 $\Delta c$ 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 $c_{\times}$ which
distinguishes the strength of the reputation effect. For publications with $c <
c_{\times}$, 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 $c\geq c_{\times}$ 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.

Physics and Society;Digital Libraries;Data Analysis, Statistics and Probability