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Gender and collaboration patterns in a temporal scientific authorship network

Journal Article · · Applied Network Science
 [1];  [1];  [2];  [3];  [4];  [5];  [1]
  1. Princeton Univ., NJ (United States)
  2. Grubhub, Inc., New York, NJ (United States); IBM, Yorktown Heights, NY (United States). Thomas J. Watson Research Center
  3. Princeton Plasma Physics Lab. (PPPL), Princeton, NJ (United States)
  4. Syracuse Univ., NY (United States)
  5. IBM, Yorktown Heights, NY (United States). Thomas J. Watson Research Center
+ Show Author Affiliations

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.

Research Organization:
Princeton Plasma Physics Laboratory (PPPL), Princeton, NJ (United States)
Sponsoring Organization:
USDOE; Simons Foundation; Princeton University
OSTI ID:
1657458
Journal Information:
Applied Network Science, Journal Name: Applied Network Science Journal Issue: 1 Vol. 4; ISSN 2364-8228
Publisher:
BioMed CentralCopyright Statement
Country of Publication:
United States
Language:
English

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Related Subjects

99 GENERAL AND MISCELLANEOUS
Authorship network
Collaboration patterns
Gender in STEM
Temporal network