Year: 2023
Type: preprint
Abstract: Citation metrics influence academic reputation and career trajectories. Recent works have highlighted flaws in citation practices in the Neurosciences, such as the under-citation of women. However, self-citation rates—or how much authors cite themselves—have not yet been comprehensively investigated in the Neurosciences. This work characterizes self-citation rates in basic, translational, and clinical Neuroscience literature by collating 157,001 articles from 63 journals between the years 2000-2020. In analyzing over eight million citations, we demonstrate four key findings: 1) since 2000, self-citation rates of Last Authors are increasing relative to those of First Authors, 2) the odds of “highly self-citing” articles from authors in the Americas are 2.65, 2.17, 1.35, and 1.43 times those of authors affiliated with Africa, Asia, Europe, and Oceania, 3) men tend to cite themselves more than women early in their careers but less later in their careers, and 4) self-citation rates vary across three major fields (Neurology, Neuroscience, Psychiatry) and 13 subfields. Our characterization of self-citation provides insight into citation practices that shape the perceived influence of authors in the Neurosciences, which in turn may impact what type of scientific research is done and who gets the opportunity to do it.
Source: eLife
Authors: Matthew Rosenblatt, Saloni Mehta, Hannah Peterson, Javid Dadashkarimi, Raimundo X. Rodriguez, Maya L. Foster, Brendan D. Adkinson, Qinghao Liang, Violet M. Kimble, Jean Ye, Marie C. McCusker, Michael C. Farruggia, Max Rolison, Margaret L. Westwater, Rongtao Jiang, Stephanie Noble, Dustin Scheinost
Institution: Yale University
Language: English
Subfield: Statistics, Probability and Uncertainty
Field: Decision Sciences
Domain: Social Sciences
Open Access status: gold
Estimated APC paid: $2,500
OpenAlex ID: W4384071955