This work presents a comprehensive research about the participation
of men and women in the area of Information and Communications
Technology (ICT) through data extracted from the last four
editions of Google Summer of Code (GSoC). The goal of this work
is to find Association Rules between gender characteristics and
coding using the Apriori Algorithm. A total of 61 association rules
were generated through the aforementioned algorithm, being 22 of
them found only in the data set with the women, 24 found only with
the men, and 15 applicable to both sets. We can cite as one of the
main findings of this work the fact that the representativeness of
women in GSoC is decreasing in the last few years. Despite this, the
representativeness of women in GSoC is above average, according
to what has been reported in other studies in the literature in which
women are underrepresented. When it comes to the most utilized
technologies, we have “Python", “Java", “C++", “C" and “JavaScript"
in the top. Analyzing technologies, it’s possible to realize that the
main utilized technologies for men and women are similar, but, in
general, men are more likely linked to programming languages.
The most common project topics are: “Event Management", “Web",
“Web Development", “Data Science" and “Cloud" in the top. This
can represent how diverse the project topics of the database are,
but not necessarily has something related to gender.