Gender Diversity on GitHub Issue Tracking: What's the Difference?




Gender on GitHub, Communication in Issue Tracking, Blau Index


This work analyzes female participation in communication on GitHub’s Issue Tracking, based on thematic relevance of posted comments according to the developer’s gender relative to other metrics, such as reputation, participation time on the platform, and number of reported issues. Data from 5 open source communities and 5 communities dedicated to women was analyzed. The results indicate that, on average, the relevance of comments made by women is similar to that of men. However, the study confirms other findings in literature that highlight low levels of female representativeness and participation in projects, with just 22% of comments posted by women and 16% of issues reported by them.


Download data is not yet available.


Araujo, A., Holanda, M., Castanho, C., Koike, C., Oliveira, R., Canedo, E., and Moro, M. (2022). Pandemia de covid-19 tem gênero. In Anais do XVI Women in Information Technology, pages 110–121, Porto Alegre, RS, Brasil. SBC.

Azevedo, B. F. T. (2011). Minerafórum : um recurso de apoio para análise qualitativa em fóruns de discussão. Tese de doutorado em informática na computação, Universidade Federal do Rio Grande do Sul.

Batista, E., e Silva, G. B., and Silva, T. (2022). Diversidade de gênero em projetos open source: um estudo da relevância dos comentários postados em issues do github. In Anais do XVI Women in Information Technology, pages 197–202, Porto Alegre, RS, Brasil. SBC.

Bertram, D., Voida, A., Greenberg, S., and Walker, R. (2010). Communication, collaboration, and bugs: The social nature of issue tracking in small, collocated teams. In Proceedings of the 2010 ACM Conference on Computer Supported Cooperative Work, CSCW ’10, pages 291–300, New York, NY, USA. ACM.

Blau, P. (1977). Inequality and Heterogeneity: A Primitive Theory of Social Structure, volume 7. Free Press.

Brandão, M. S., Godinho-Filho, M., Azzolini Junior, W., Battissacco, B. C., and Astorino Marçola, J. (2022). Melhoria da categorização de produtos a partir do uso de algoritmos de aprendizado de máquina e medidas de similaridade. Revista Produção Online, 21(4):2093–2124.

Canedo, E., Tives, H., Bogo, M., Fagundes, F., and Siqueira de Cerqueira, J. (2019). Barriers faced by women in software development projects. Information, 10:309.

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 41st International Conference on Software Engineering: Software Engineering in Society (ICSESEIS), pages 11–20, Montreal, QC, Canada. IEEE.

Izquierdo, D., Huesman, N., Serebrenik, A., and Robles, G. (2019). Openstack gender diversity report. IEEE Software, 36:28–33.

Machado, C. J. R., Maciel, A. M. A., Rodrigues, R. L., and Menezes, R. (2019). An approach for thematic relevance analysis applied to textual contributions in discussion forums. International Journal of Distance Education Technologies, 17:37–51.

Medeiros, D. C., de Queiroz, J. E. R., and Araújo, J. M. F. R. (2014). Análise de funções de similaridade para verificação do conteúdo de mensagens em fóruns de discussão. In Brazilian Symposium on Computers in Education (Simpósio Brasileiro de Informática na Educação - SBIE), number 1, page 144, Dourados, Mato Grosso do Sul, Brazil. SBC.

Neto, L., Silva, G., and Comarela, G. (2021). Estimativa do tempo de resolução de issues no github usando atributos textuais e temporais. In Brazilian Symposium on Software Engineering, page 253–262, New York, NY, USA. Association for Computing Machinery.

Neto, L. E. C. and Silva, G. B. e. (2018). Colminer: A tool to support communications management in an issue tracking environment. In Proceedings of the XIV Brazilian Symposium on Information Systems, SBSI’18, New York, NY, USA. Association for Computing Machinery.

Noei, E. and Lyons, K. (2022). A study of gender in user reviews on the google play store. Empirical Softw. Engg., 27(2).

Ortu, M., Hall, T., Marchesi, M., Tonelli, R., Bowes, D., and Destefanis, G. (2018). Mining communication patterns in software development: A github analysis. In Proceedings of the 14th International Conference on Predictive Models and Data Analytics in Software Engineering, PROMISE’18, page 70–79, New York, NY, USA. Association for Computing Machinery.

Outão, J. C. S. d. and Santos, R. P. d. (2022). How does diversity manifest itself in software ecosystems? In XVIII Brazilian Symposium on Information Systems, SBSI, New York, NY, USA. Association for Computing Machinery.

Outão, J. and Santos, R. (2022). Investigando fatores da diversidade de gênero nos ecossistemas de software. In Anais Estendidos do XVIII Simpósio Brasileiro de Sistemas de Informação, pages 53–58, Porto Alegre, RS, Brasil. SBC

Paranhos, R., Figueiredo Filho, D. B., Rocha, E. C. d., Silva Júnior, J. A. d., Neves, J. A. B., and Santos, M. L. W. D. (2014). Desvendando os mistérios do coeficiente de correlação de pearson: o retorno. Leviathan (São Paulo), (8):66–95.

Qiu, H. S., Li, Y. L., Padala, S., Sarma, A., and Vasilescu, B. (2019). The signals that potential contributors look for when choosing open-source projects. Proc. ACM Hum. Comput. Interact., 3(CSCW).

Rodriguez, G., Nadri, R., and Nagappan, M. (2021). Perceived diversity in software engineering: a systematic literature review. Empirical Software Engineering, 26.

Saadat, S., Newton, O. B., Sukthankar, G., and Fiore, S. M. (2020). Analyzing the productivity of github teams based on formation phase activity. In 2020 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT), pages 169–176, Melbourne, Australia. IEEE.

Singh, V. (2019). Women-only spaces of open source. In 2019 IEEE/ACM 2nd International Workshop on Gender Equality in Software Engineering (GE), pages 17–20, Montreal, QC, Canada. IEEE.

Steinmacher, I., Wiese, I. S., Chaves, A. P., and Gerosa, M. A. (2012). Newcomers withdrawal in open source software projects: Analysis of hadoop common project. In 2012 Brazilian Symposium on Collaborative Systems, pages 65–74.

Vasilescu, B., Serebrenik, A., and Filkov, V. (2015). A data set for social diversity studies of github teams. In 2015 IEEE/ACM 12th Working Conference on Mining Software Repositories, pages 514–517, Florence, Italy. IEEE.

Vedres, B. and Vasarhelyi, O. (2019). Gendered behavior as a disadvantage in open source software development. EPJ Data Science, 8.

Zacchiroli, S. (2021). Gender differences in public code contributions: A 50-year perspective. IEEE Software, 38(2):45–50.

Zolduoarrati, E. and Licorish, S. A. (2021). On the value of encouraging gender tolerance and inclusiveness in software engineering communities. Information and Software Technology, 139:106667.


Additional Files



How to Cite

BATISTA, E. M.; SILVA, G. B. e; SILVA, T. R. de M. B. e. Gender Diversity on GitHub Issue Tracking: What’s the Difference?. Journal on Interactive Systems, Porto Alegre, RS, v. 14, n. 1, p. 128–137, 2023. DOI: 10.5753/jis.2023.3126. Disponível em: Acesso em: 1 oct. 2023.



Regular Paper