Exploring the Role of Women in Hugging Face Organizations
Resumo
Background: Despite its impact on innovation, gender diversity remains far from fully being achieved in open-source projects. Aims: We examine gender diversity in Hugging Face (HF) organizations, investigating its impact on innovation and team dynamics in open-source development projects. Method: We conducted a repository mining study, focusing on ML model development projects on HF, to explore the involvement of women in collaborative processes. Results: Women are highly underrepresented in both organizations and commits distribution, which is also found when analyzing individual developers. Conclusions: Addressing gender disparities is essential to create more equitable, diverse, and inclusive open-source ecosystems.
Palavras-chave:
Hugging Face, Repository mining, Commit, Organization, Gender, Social sustainability
Referências
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American Psychological Association (2015). Key Terms and Concepts in Understanding Gender Diversity and Sexual Orientation Among Students.
Basili, V. R., Caldiera, G., and Rombach, H. D. (1994). The Goal Question Metric approach. Encyclopedia of software engineering, pages 528–532.
Castaño, J., Martínez-Fernández, S., Franch, X., and Bogner, J. (2024). Analyzing the Evolution and Maintenance of ML Models on Hugging Face. MSR ’24, page 607–618.
Catolino, G., Palomba, F., Tamburri, D. A., Serebrenik, A., and Ferrucci, F. (2019). Gender Diversity and Women in Software Teams: How Do They Affect Community Smells? In 2019 IEEE/ACM ICSE-SEIS, pages 11–20.
Cohen, J. (1960). A coefficient of agreement for nominal scales. Educational and psychological measurement, 20(1):37–46.
Damian, D., Blincoe, K., Ford, D., Serebrenik, A., and Masood, Z. (2024). Equity, Diversity, and Inclusion in Software Engineering: Best Practices and Insights. Springer.
De Martino, V., Castaño, J., Palomba, F., Franch, X., and Martínez-Fernández, S. (2025). A Framework for Using LLMs for Repository Mining Studies in Empirical Software Engineering. WSESE@ICSE 2025.
Gomathy, D. (2023). Workplace Diversity and its effects on team dynamics and productivity. Intl journal of scientific research in engineering and management, 7(06):1–8.
Hodges, M. and Murphy-Hill, E. (2024). Perceptions of Software Developer Inclusion: A Survey at Google. In Equity, Diversity, and Inclusion in Software Engineering: Best Practices and Insights (pp. 207-230).
Imtiaz, N., Middleton, J., Chakraborty, J., Robson, N., Bai, G., and Murphy-Hill, E. (2019). Investigating the Effects of Gender Bias on GitHub. In 2019 IEEE/ACM ICSE, pages 700–711.
Kohl, K. and Prikladnicki, R. (2022). Benefits and Difficulties of Gender Diversity on Software Development Teams: A Qualitative Study. In SBES’22, 21–30.
Kohl, K. and Prikladnicki, R. (2024). Gender Diversity on Software Development Teams: A Qualitative Study. In Equity, Diversity, and Inclusion in Software Engineering: Best Practices and Insights (pp. 169-184).
Krishnan and Gokula, D. S. (2020). Gender Diversity in the workplace and its effects on Employees’ Performance. Journal of the Social Sciences.
Lanubile, F., Martínez-Fernández, S., and Quaranta, L. (2024). Training Future Machine Learning Engineers: A Project-Based Course on MLOps. IEEE Software, 41(2):60– 67.
Palomba, F., Tamburri, D. A., Serebrenik, A., Zaidman, A., Fontana, F. A., and Oliveto, R. (May 2018). How do community smells influence code smells? In ICSE 2018, pages 240–241.
Phillips, K. and O’Reilly, C. (1998). Demography and Diversity in Organizations: A Review of 40 Years of Research, volume 20, pages 77–140.
Rastogi, A. (2024). Roads Ahead to Diversity and Inclusion by Software Engineering. In Equity, Diversity, and Inclusion in Software Engineering: Best Practices and Insights (pp. 3-16).
Serebrenik, A. (2024). How to Ask About Gender Identity of Software Engineers and “Guess” It from the Archival Data. In Equity, Diversity, and Inclusion in Software Engineering: Best Practices and Insights (pp. 487-505).
Stack-Overflow (2022). Stack Overflow Developer Survey. [link].
Storey, M.-A., Ernst, N. A., Williams, C., and Kalliamvakou, E. (2020). The who, what, how of software engineering research: a socio-technical framework. Empirical Software Engineering, 25:4097–4129.
Valoatto, M. Top Contributors To Follow - a Hugging Face Space by mvaloatto — huggingface. co. [link]. [Accessed 30-01-2025].
Vasilescu, B., Posnett, D., Ray, B., van den Brand, M. G., Serebrenik, A., Devanbu, P., and Filkov, V. (2015). Gender and Tenure Diversity in GitHub Teams. CHI ’15, page 3789–3798.
Williams, J. C. and Dempsey, R. (2014). What works for women at work: Four patterns working women need to know. In What Works for Women at Work. New York University Press.
American Psychological Association (2015). Key Terms and Concepts in Understanding Gender Diversity and Sexual Orientation Among Students.
Basili, V. R., Caldiera, G., and Rombach, H. D. (1994). The Goal Question Metric approach. Encyclopedia of software engineering, pages 528–532.
Castaño, J., Martínez-Fernández, S., Franch, X., and Bogner, J. (2024). Analyzing the Evolution and Maintenance of ML Models on Hugging Face. MSR ’24, page 607–618.
Catolino, G., Palomba, F., Tamburri, D. A., Serebrenik, A., and Ferrucci, F. (2019). Gender Diversity and Women in Software Teams: How Do They Affect Community Smells? In 2019 IEEE/ACM ICSE-SEIS, pages 11–20.
Cohen, J. (1960). A coefficient of agreement for nominal scales. Educational and psychological measurement, 20(1):37–46.
Damian, D., Blincoe, K., Ford, D., Serebrenik, A., and Masood, Z. (2024). Equity, Diversity, and Inclusion in Software Engineering: Best Practices and Insights. Springer.
De Martino, V., Castaño, J., Palomba, F., Franch, X., and Martínez-Fernández, S. (2025). A Framework for Using LLMs for Repository Mining Studies in Empirical Software Engineering. WSESE@ICSE 2025.
Gomathy, D. (2023). Workplace Diversity and its effects on team dynamics and productivity. Intl journal of scientific research in engineering and management, 7(06):1–8.
Hodges, M. and Murphy-Hill, E. (2024). Perceptions of Software Developer Inclusion: A Survey at Google. In Equity, Diversity, and Inclusion in Software Engineering: Best Practices and Insights (pp. 207-230).
Imtiaz, N., Middleton, J., Chakraborty, J., Robson, N., Bai, G., and Murphy-Hill, E. (2019). Investigating the Effects of Gender Bias on GitHub. In 2019 IEEE/ACM ICSE, pages 700–711.
Kohl, K. and Prikladnicki, R. (2022). Benefits and Difficulties of Gender Diversity on Software Development Teams: A Qualitative Study. In SBES’22, 21–30.
Kohl, K. and Prikladnicki, R. (2024). Gender Diversity on Software Development Teams: A Qualitative Study. In Equity, Diversity, and Inclusion in Software Engineering: Best Practices and Insights (pp. 169-184).
Krishnan and Gokula, D. S. (2020). Gender Diversity in the workplace and its effects on Employees’ Performance. Journal of the Social Sciences.
Lanubile, F., Martínez-Fernández, S., and Quaranta, L. (2024). Training Future Machine Learning Engineers: A Project-Based Course on MLOps. IEEE Software, 41(2):60– 67.
Palomba, F., Tamburri, D. A., Serebrenik, A., Zaidman, A., Fontana, F. A., and Oliveto, R. (May 2018). How do community smells influence code smells? In ICSE 2018, pages 240–241.
Phillips, K. and O’Reilly, C. (1998). Demography and Diversity in Organizations: A Review of 40 Years of Research, volume 20, pages 77–140.
Rastogi, A. (2024). Roads Ahead to Diversity and Inclusion by Software Engineering. In Equity, Diversity, and Inclusion in Software Engineering: Best Practices and Insights (pp. 3-16).
Serebrenik, A. (2024). How to Ask About Gender Identity of Software Engineers and “Guess” It from the Archival Data. In Equity, Diversity, and Inclusion in Software Engineering: Best Practices and Insights (pp. 487-505).
Stack-Overflow (2022). Stack Overflow Developer Survey. [link].
Storey, M.-A., Ernst, N. A., Williams, C., and Kalliamvakou, E. (2020). The who, what, how of software engineering research: a socio-technical framework. Empirical Software Engineering, 25:4097–4129.
Valoatto, M. Top Contributors To Follow - a Hugging Face Space by mvaloatto — huggingface. co. [link]. [Accessed 30-01-2025].
Vasilescu, B., Posnett, D., Ray, B., van den Brand, M. G., Serebrenik, A., Devanbu, P., and Filkov, V. (2015). Gender and Tenure Diversity in GitHub Teams. CHI ’15, page 3789–3798.
Williams, J. C. and Dempsey, R. (2014). What works for women at work: Four patterns working women need to know. In What Works for Women at Work. New York University Press.
Publicado
12/05/2025
Como Citar
SALINAS, Maria Tubella; GONZÁLEZ, Alexandra; MARTÍNEZ-FERNÁNDEZ, Silverio.
Exploring the Role of Women in Hugging Face Organizations. In: CONGRESSO IBERO-AMERICANO EM ENGENHARIA DE SOFTWARE (CIBSE), 28. , 2025, Ciudad Real/Espanha.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2025
.
p. 75-89.
DOI: https://doi.org/10.5753/cibse.2025.35293.
