# Reputation and Impact in Academic Careers

arXiv: https://arxiv.org/abs/1303.7274 · HTML: https://mlsanity.com/paper/1303.7274/

## Key facts

- Cited by 7 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 29 Mar 2013.

## Built on by (most cited first, 7 of 7)

- [Leveraging LLM-based agents for social science research: insights from citation network simulations](https://mlsanity.com/paper/2511.03758/) (2025)
- [Citation Amnesia: On The Recency Bias of NLP and Other Academic Fields](https://mlsanity.com/paper/2402.12046/) (2024)
- [A Measure of Research Taste](https://mlsanity.com/paper/2105.08089/) (2021)
- [Biases in Scholarly Recommender Systems: Impact, Prevalence, and Mitigation](https://mlsanity.com/paper/2301.07483/) (2023)
- [ChatGPT cites the most-cited articles and journals, relying solely on Google Scholar's citation counts. As a result, AI may amplify the Matthew Effect in environmental science](https://mlsanity.com/paper/2304.06794/) (2023)
- [Minorities in networks and algorithms](https://mlsanity.com/paper/2206.07113/) (2022)
- [The Future of NLP may not be at NLP Conferences: Scholarly Migration Patterns in Natural Language Processing](https://mlsanity.com/paper/2607.02416/) (2026)

## Abstract (arXiv)

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 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.