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Data for the paper: Gender Inequities in the Online Dissemination of Scholars’ Work

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Gender Inequities in the Online Dissemination of Scholars’ Work

Unbiased science dissemination has the potential to alleviate some of the known gender disparities in academia by exposing female scholars' work to other scientists and the public. And yet, we lack comprehensive understanding of the relationship between gender and science dissemination online. Our large-scale analyses, encompassing half a million scholars, revealed that female scholars' work is mentioned less frequently than male scholars' work in all research areas. When exploring the characteristics associated with online success, we found that the impact of prior work, social capital, and gendered tie formation in co-authorship networks are linked with online success for men, but not for women--even in the areas with the highest female representation. These results suggest that while men's scientific impact and collaboration networks are associated with higher visibility online, there are no universally identifiable facets associated with success for women. Our comprehensive empirical evidence indicates that the gender gap in online science dissemination is coupled with a lack of understanding the characteristics that are linked with female scholars' success, which might hinder efforts to close the gender gap in visibility.

Keywords: gender inequality, scholarly communication, social networks, STEM, computational social science

Citation: O. Vásárhelyi, I Zakhlebin, S. Milojevic, E-Á. Horvát. "Gender Inequities in the Online Dissemination of Scholars’ Work". PNAS 2021 vol. 118 e2102945118 DOI: https://doi.org/10.1073/pnas.2102945118

DATABASE DESCRIPTION

Data files are provided for each broad research area and contain variables capturing scientists' offline and online activity. We used these measures to evaluate and model the online success of scholars. Broad research areas were inferred from Web of Science data provided by Clarivate Analytics, at a cost. In addition, affiliates of member institutions can access Web of Science data for free through CADRE. The algorithm used for classifying broad research areas is accessible here (Figure 2). The number of online shares of scientists' articles was obtained through Altmetric's free Researcher Data Access Program. Metrics of scientists' ego networks were collected from the Open Academic Graph dataset.

Variables:

  • Author ID
  • Female
  • Successful (Top 25%)
  • Number of shares
  • Social Capital (PCA)
  • Network Femaleness (PCA)
  • Network Maleness (PCA)
  • Scientific Impact (PCA)
  • H-index 2012
  • Num. papers (last 5 years)
  • Impact factor
  • High impact journal
  • Ego network degree
  • Ego network density
  • Num. collaborators (last 5 years)
  • Num. papers in female majority teams
  • Female homophily
  • Tie strength to women
  • Num. papers in male majority teams
  • Male homophily
  • Tie strength to men

If you have qustion about the databases contact: Orsolya Vasarhelyi (orsolya.vasarhelyi@gmail.com) Last updated: 2021-08-24

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