Gender differences in participation and reward on Stack Overflow

May, Anna; Wachs, Johannes; Hannák, Anikó

doi:10.1007/s10664-019-09685-x

Cited by 77 publications

(45 citation statements)

References 55 publications

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“…More specifically, it contains the most popular content sharing sites for software developers, i.e., GitHub and the most well-known Q&A Stack Overflow. Job seekers in the software engineering sector are often asked whether they have a Stack Overflow or GitHub account [103]. Having an account could be an asset for a candidate, as it helps hiring managers to evaluate an applicant's expertise level.…”

Section: Resultsmentioning

confidence: 99%

Extracting Knowledge From On-Line Sources for Software Engineering Labor Market: A Mapping Study

et al. 2019

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Software engineering is a continuously evolving sector and the demands of the related labor market result in a wide variety of job openings, ranging from developers to customer service positions. Thus, there is a need to continuously monitor labor market trends using data and analytics. Both employers and employees can benefit by capturing emerging trends which can facilitate continuous learning and training in new technologies, support of better matching between a job offer and the ideal candidate and expertise detection. To fulfill these needs, the results of labor market analytics need to reach the stakeholders timely and accurately. However, often delays occur, which stem from time-consuming approaches based on collecting data from traditional sources, such as questionnaires or interviews. Recently, researchers started leveraging content from digital sources, which are easily accessed and contain a wealth of information. This paper presents the results of a Systematic Mapping Study on digital sources that can be used to address the data analytics needs of the labor market. It provides a multifaceted categorization of the issues involved in the analysis of digital sources of the software engineering labor market. It aims to identify digital labor market sources for data retrieval which are appropriate for employers and employees analytics. Additionally, it aims to connect different skill types, needs and goals of labor market with the utilization of digital sources and data analysis methods. In total 86 primary studies were selected and each one was evaluated and classified aiming to identify the: (a) digital sources that are used for labor market analytics; (b) type of skills they examine; (c) methods which are used to utilize the raw digital content; (d) goals for which every primary study is conducted; (e) beneficiaries (stakeholder) of the results; and (f) time trends for all the above.

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Section: Resultsmentioning

confidence: 99%

Extracting Knowledge From On-Line Sources for Software Engineering Labor Market: A Mapping Study

et al. 2019

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“…This "gender confidence gap" grows as students take more advanced courses (Alvarado, Cao, & Minnes, 2017). Additionally, analyses of communal academic COURSE REVIEWS AND GENDER DIFFERENCES 8 resources in CS programs find substantial differences in how contributions by male and female users are acknowledged in Github and StackOverflow (May, Wachs, & Hannák, 2019) (Terrell et al, 2017). Course reviews may provide additional insight into gender variance in how students make sense of their academic exposure to computer science.…”

Section: Gender and Care Work In Course Reviewsmentioning

confidence: 99%

Course reviews reveal gender differences and other scientific insight about the students who submit them

Lang¹,

Chen²,

Paepcke³

et al. 2020

Preprint

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Student course reviews are rarely considered as research instruments, yet their ubiquity makes them potentially powerful tools for education data science. To illustrate this potential we utilize a corpus of 11,255 reviews of computer science courses submitted by students at a private research university to observe how students appraise their own learning and give advice to future students. We recover evidence of gendered self-perceptions and care-giving strategies in Computer Science courses. Among submitters: females understate their achievement of learning goals relative to males earning the same grades; females offer lengthier written advice to future students than males; advice written by females exhibits more positive tone. Findings affirm the potential of leveraging course reviews for archival, survey, and quasi-experimental research investigations going forward

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“…In the work developed by May et al [23] the gender differences in activities and user success in Stack Overflow were investigated. Women are highly underrepresented, not only in comparison to male users, but also in relation to their presence in the Information Technology job market.…”

Section: Related Workmentioning

confidence: 99%

Barriers Faced by Women in Software Development Projects

Canedo

Leão²,

Marioti³

et al. 2019

Information

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Computer science is a predominantly male field of study. Women face barriers while trying to insert themselves in the study of computer science. Those barriers extend to when women are exposed to the professional area of computer science. Despite decades of social fights for gender equity in Science, Technology, Engineering, and Mathematics (STEM) education and in computer science in general, few women participate in computer science, and some of the reasons include gender bias and lack of support for women when choosing a computer science career. Open source software development has been increasingly used by companies seeking the competitive advantages gained by team diversity. This diversification of the characteristics of team members includes, for example, the age of the participants, the level of experience, education and knowledge in the area, and their gender. In open source software projects women are underrepresented and a series of biases are involved in their participation. This paper conducts a systematic literature review with the objective of finding factors that could assist in increasing women’s interest in contributing to open source communities and software development projects. The main contributions of this paper are: (i) identification of factors that cause women’s lack of interest (engagement), (ii) possible solutions to increase the engagement of this public, (iii) to outline the profile of professional women who are participating in open source software projects and software development projects. The main findings of this research reveal that women are underrepresented in software development projects and in open source software projects. They represent less than 10% of the total developers and the main causes of this underrepresentation may be associated with their workplace conditions, which reflect male gender bias.

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Gender differences in participation and reward on Stack Overflow

Cited by 77 publications

References 55 publications

Extracting Knowledge From On-Line Sources for Software Engineering Labor Market: A Mapping Study

Extracting Knowledge From On-Line Sources for Software Engineering Labor Market: A Mapping Study

Course reviews reveal gender differences and other scientific insight about the students who submit them

Barriers Faced by Women in Software Development Projects

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