Gender and collaboration patterns in a temporal scientific authorship network

Gecia Bravo-Hermsdorff, Valkyrie Felso, Emily Ray, Lee M. Gunderson, Mary E. Helander, Joana Maria, Yael Niv

Research output: Contribution to journalReview articlepeer-review

14 Scopus citations

Abstract

One can point to a variety of historical milestones for gender equality in STEM (science, technology, engineering, and mathematics), however, practical effects are incremental and ongoing. It is important to quantify gender differences in subdomains of scientific work in order to detect potential biases and monitor progress. In this work, we study the relevance of gender in scientific collaboration patterns in the Institute for Operations Research and the Management Sciences (INFORMS), a professional society with sixteen peer-reviewed journals. Using their publication data from 1952 to 2016, we constructed a large temporal bipartite network between authors and publications, and augmented the author nodes with gender labels. We characterized differences in several basic statistics of this network over time, highlighting how they have changed with respect to relevant historical events. We find a steady increase in participation by women (e.g., fraction of authorships by women and of new women authors) starting around 1980. However, women still comprise less than 25% of the INFORMS society and an even smaller fraction of authors with many publications. Moreover, we describe a methodology for quantifying the structural role of an authorship with respect to the overall connectivity of the network, using it to measure subtle differences between authorships by women and by men. Specifically, as measures of structural importance of an authorship, we use effective resistance and contraction importance, two measures related to diffusion throughout a network. As a null model, we propose a degree-preserving temporal and geometric network model with emergent communities. Our results suggest the presence of systematic differences between the collaboration patterns of men and women that cannot be explained by only local statistics.

Original languageEnglish (US)
Article number112
JournalApplied Network Science
Volume4
Issue number1
DOIs
StatePublished - Dec 1 2019

All Science Journal Classification (ASJC) codes

  • General
  • Computer Networks and Communications
  • Computational Mathematics

Keywords

  • Authorship network
  • Collaboration patterns
  • Gender in STEM
  • Temporal network

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