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  • Item type:Publication,
    Gender Differences in Collaboration Patterns in Computer Science Open PDF 
    (2022)
    Yamamoto, J.
    ;
    Frachtenberg, E.
    The research discipline of computer science (CS) has a well-publicized gender disparity. Multiple studies estimate the ratio of women among publishing researchers to be around 15–30%. Many explanatory factors have been studied in association with this gender gap, including differences in collaboration patterns. Here, we extend this body of knowledge by looking at differences in collaboration patterns specific to various fields and subfields of CS. We curated a dataset of nearly 20,000 unique authors of some 7000 top conference papers from a single year. We manually assigned a field and subfield to each conference and a gender to most researchers. We then measured the gender gap in each subfield as well as five other collaboration metrics, which we compared to the gender gap. Our main findings are that the gender gap varies greatly by field, ranging from 6% female authors in theoretical CS to 42% in CS education; subfields with a higher gender gap also tend to exhibit lower female productivity, larger coauthor groups, and higher gender homophily. Although women published fewer single-author papers, we did not find an association between single-author papers and the ratio of female researchers in a subfield. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.
  • Item type:Publication,
    Mind the gap gender and computer science conferences
    (2018)
    Van Herck, S.
    ;
    Fiscarelli, A.M.
    Computer science research areas are often arbitrarily defined by researchers themselves based on their own opinions or conference rankings. First, we aim to classify conferences in computer science in an automated and objective way based on topic modelling. We then study the topic relatedness of research areas to identify isolated disciplinary silos and clusters that display more interdisciplinarity and collaboration. Furthermore, we compare career length, publication growth rate and collaboration patterns for men and women in these research areas. © IFIP International Federation for Information Processing 2018.
  • Item type:Publication,
    Scientometric Analysis of Interdisciplinary Collaboration and Gender Trends in 30 Years of IEEE VIS Publications Open PDF 
    (2022)
    Sarvghad, A.
    ;
    Franqui-Nadal, R.
    ;
    Reznik-Zellen, R.
    ;
    Chawla, R.
    ;
    Mahyar, N.
    We present the results of a scientometric analysis of 30 years of IEEE VIS publications between 1990-2020, in which we conducted a multifaceted analysis of interdisciplinary collaboration and gender composition among authors. To this end, we curated BiblioVIS, a bibliometric dataset that contains rich metadata about IEEE VIS publications, including 3032 papers and 6113 authors. One of the main factors differentiating BiblioVIS from similar datasets is the authors' gender and discipline data, which we inferred through iterative rounds of computational and manual processes. Our analysis shows that, by and large, inter-institutional and interdisciplinary collaboration has been steadily growing over the past 30 years. However, interdisciplinary research was mainly between a few fields, including Computer Science, Engineering and Technology, and Medicine and Health disciplines. Our analysis of gender shows steady growth in women's authorship. Despite this growth, the gender distribution is still highly skewed, with men dominating (~75%) of this space. Our predictive analysis of gender balance shows that if the current trends continue, gender parity in the visualization field will not be reached before the third quarter of the century (~2070). Our primary goal in this work is to call the visualization community's attention to the critical topics of collaboration, diversity, and gender. Our research offers critical insights through the lens of diversity and gender to help accelerate progress towards a more diverse and representative research community. IEEE
  • Item type:Publication,
    Representation of women in HPC conferences
    (2021)
    Frachtenberg, E.
    ;
    Kaner, R.D.
    Women are acutely underrepresented in the HPC workforce. Addressing this gap requires accurate metrics on the representation of women and its associated factors. The goal of this paper is to provide current, broad, and reproducible data on this gender gap. Specifically, this study provides in-depth statistics on women s representation in HPC conferences, especially for authors of peer-reviewed papers, who serve as the keystone for future advances in the field. To this end, we analyzed participant data from nine HPC and HPC-related peer-reviewed conferences. In addition to gender distributions, we looked at post-publication citation statistics of the papers and authors research experience, country, and work sector. Our main finding is that women represent only 10% of all HPC authors, with large geographical variations and small variations by sector. Representation is particularly low at higher experience levels. This 10% ratio is lower than even the 20 30% ratio in all computer science. © 2021 IEEE Computer Society. All rights reserved.
  • Item type:Publication,
    Underrepresentation of women in computer systems research Open PDF 
    (2022)
    Frachtenberg, E.
    ;
    Kaner, R.D.
    The gender gap in computer science (CS) research is a well-studied problem, with an estimated ratio of 15%–30% women researchers. However, far less is known about gender representation in specific fields within CS. Here, we investigate the gender gap in one large field, computer systems. To this end, we collected data from 72 leading peer-reviewed CS conferences, totalling 6,949 accepted papers and 19,829 unique authors (2,946 women, 16,307 men, the rest unknown). We combined these data with external demographic and bibliometric data to evaluate the ratio of women authors and the factors that might affect this ratio. Our main findings are that women represent only about 10% of systems researchers, and that this ratio is not associated with various conference factors such as size, prestige, double-blind reviewing, and inclusivity policies. Author research experience also does not significantly affect this ratio, although author country and work sector do. The 10% ratio of women authors is significantly lower than the 16% in the rest of CS. Our findings suggest that focusing on inclusivity policies alone cannot address this large gap. Increasing women’s participation in systems research will require addressing the systemic causes of their exclusion, which are even more pronounced in systems than in the rest of CS. © 2022 Frachtenberg, Kaner. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
  • Item type:Publication,
    Trends in authorship by women at Canadian universities 2006 to 2019 Open PDF 
    (Canadian Association for Information Science - Association canadienne des sciences de l'information, 2021)
    Demaine, Jeffrey
    Despite much progress since the mid-20th century, there still exists a disparity in the number of female academics relative to their male colleagues. This gender gap has come under increased focus as universities take steps to foster diversity and inclusiveness. Bibliometrics can provide a window into the gender disparity in research by measuring the metadata of academic publications. By determining the ratio of female to male authors, the gender bias at the level of the institution can be quantified. This study examines the proportion of female authors of academic articles at thirty Canadian universities across five broad fields of research.