iSchool researchers explore gender gap in self-citations

Vetle Torvik
Vetle Torvik, Associate Professor
Jana Diesner
Jana Diesner, Affiliate Associate Professor

A recent publication by a group of iSchool researchers provides new insight into the claim that men self-cite their publications more often than their women counterparts. The paper, "Self-citation is the hallmark of productive authors, of any gender," coauthored by doctoral student Shubhanshu Mishra, Brent Fegley (MS/LIS '10, PhD Informatics '16), Associate Professor Jana Diesner, and Associate Professor Vetle Torvik, was published in PLOS ONE on September 26 and selected as an Editor’s Pick by PLOS Collections.

To replicate the gender gap, the researchers used a probabilistic model of self-citation based on over 1.6 million papers in PubMed with two or more authors, in which 5.5 million of the 41.6 million citations are self-citations. They found that gender has the weakest effect on the probability of self-citation among the features tested, including byline position, affiliation, ethnicity, collaboration size, time lag, subject-matter novelty, reference/citation counts, publication type, language, and venue. The features that explain most self-citations have more to do with opportunity, accessibility, and visibility than gender and culture.

Citations boost the visibility of a paper as well as the paper's author and are an essential part of scientific communication. While a gender effect exists, the researchers state that it is certainly not the "gender gap" previously noted. They conclude that self-citation is the hallmark of productive authors of any gender.

Research reported in the publication was supported in part by the National Institute on Aging of the NIH (Award Number P01AG039347) and the Directorate for Education & Human Resources of the NSF (Award Number 1348742). 

Updated on
Backto the news archive

Related News

Ocepek and Sanfilippo co-edit book on misinformation

Assistant Professor Melissa Ocepek and Assistant Professor Madelyn Rose Sanfilippo have co-edited a new book, Governing Misinformation in Everyday Knowledge Commons, which was recently published by Cambridge University Press. An open access edition of the book is available, thanks to support from the Governing Knowledge Commons Research Coordination Network (NSF 2017495). The new book explores the socio-technical realities of misinformation in a variety of online and offline everyday environments. 

Governing Misinformation in Everyday Knowledge Commons book

Faculty receive support for AI-related projects from new pilot program

Associate Professor Yun Huang, Assistant Professor Jiaqi Ma, and Assistant Professor Haohan Wang have received computing resources from the National Artificial Intelligence Research Resource (NAIRR), a two-year pilot program led by the National Science Foundation in partnership with other federal agencies and nongovernmental partners. The goal of the pilot is to support AI-related research with particular emphasis on societal challenges. Last month, awardees presented their research at the NAIRR Pilot Annual Meeting.

iSchool participation in iConference 2025

The following iSchool faculty and students will participate in iConference 2025, which will be held virtually from March 11-14 and physically from March 18-22 in Bloomington, Indiana. The theme of this year's conference is "Living in an AI-gorithmic world."

Carboni joins the iSchool faculty

The iSchool is pleased to announce that Nicola Carboni has joined the faculty as an assistant professor. He previously served as a postdoctoral researcher and lecturer in digital humanities at the University of Geneva.

Nicola Carboni

Youth-AI-Safety named a winning team in international hackathon

A team of researchers from the SALT (Social Computing Systems) Lab has been selected as a winner in an international hackathon hosted by the Berkeley Center for Responsible, Decentralized Intelligence. The LLM Agents MOOC Hackathon brought together over 3,000 students, researchers, and practitioners from 127 countries to build and showcase innovative work in large language model (LLM) agents, grow the AI agent community, and advance LLM agent technology.