Gender Differences in Participation and Reward on Stack Overflow

Programming is a valuable skill in the labor market, making the underrepresentation of women in computing an increasingly important issue. Online question and answer platforms serve a dual purpose in this field: they form a body of knowledge useful as a reference and learning tool, and they provide opportunities for individuals to demonstrate credible, verifiable expertise. Issues, such as male-oriented site design or overrepresentation of men among the site's elite may therefore compound the issue of women's underrepresentation in IT. In this paper we audit the differences in behavior and outcomes between men and women on Stack Overflow, the most popular of these Q&A sites. We observe significant differences in how men and women participate in the platform and how successful they are. For example, the average woman has roughly half of the reputation points, the primary measure of success on the site, of the average man. Using an Oaxaca-Blinder decomposition, an econometric technique commonly applied to analyze differences in wages between groups, we find that most of the gap in success between men and women can be explained by differences in their activity on the site and differences in how these activities are rewarded. Specifically, 1) men give more answers than women and 2) are rewarded more for their answers on average, even when controlling for possible confounders such as tenure or buy-in to the site. Women ask more questions and gain more reward per question. We conclude with a hypothetical redesign of the site's scoring system based on these behavioral differences, cutting the reputation gap in half

Trouble in programmer's paradise: gender biases in sharing and recognising technical knowledge on Stack Overflow

This paper examines gender-biases on Stack Overflow, the world’s largest question-and-answer forum of programming knowledge. Employing a non-binary gender identification built on usernames, I investigate the role of gender in shaping users’ experience in technical forums. The analysis encompasses 11-years of activity, across levels of expertise, language, and specialism, to assess if Stack Overflow is really a paradise for programmers. I first examine individual users, asking if there are gender differences in key user metrics of success, focusing on reputation points, user tenure, and level of activity. Second, I test if there are gender-biases in how technical knowledge is recognised in the question-answer format of the platform. Third, using social network analysis I investigate if interaction on Stack Overflow is organised by gender. Results show that sharing and recognising technical knowledge is dictated by users’ gender, even when it is operationalised beyond a binary. I find that feminine users receive lower scores for their answers, despite exhibiting higher effort in their contributions. I also show that interaction on Stack Overflow is organised by gender. Specifically, that feminine users preferentially interact with other feminine users. The findings emphasise the central role of gender in shaping interaction in technical spaces, a necessity for participation in the masculine-dominated forum. I conclude the study with recommendations for inclusivity in online forums

Collaborating neuroscience online: The case of the Human Brain Project forum

This paper analyzes user interactions on the public-access online forum of the Human Brain Project (HBP), a major European Union-funded neuroscience research initiative, to understand the utility of the Forum for collaborative problem solving. We construct novel data using discussion forum posts and detailed user profiles on the HBP Forum. We find that HBP Forum utilization is comparable to that of a leading general-interest coding platform, and that online usage metrics quickly recovered after an initial Covid-19-related dip. Regression results show that user interactions on the Forum are more active for questions on programming and in HBP core areas. Further, Cox proportional hazard analyses show that such problems are solved faster. Forum posts with users from different countries tend to be discussed more actively but solved slower. Higher shares of administrator support tend to solve problems faster. There are no clear patterns regarding gender and seniority. Our results suggest that building novel collaborative forums can support researchers working on complex topics in challenging times

Giving and Taking in Online Communities of Practice: The Role of Geography and Culture in Knowledge Sharing and Innovation

Researchers have long been fascinated with the phenomenon of lurking and free riding in knowledge sharing. This interest has led to the investigation of which factors drive decisions to contribute to a knowledge exchange as opposed to only exploiting the information in such exchange. Many studies have specifically focused on identifying the extrinsic and intrinsic motivational drivers for knowledge sharing in communities of practice by administering user surveys on behavioral intention, expectations, and satisfaction with the community. Our analysis is different from prior studies in that it does not look at expectations of reciprocity and other individual characteristics. Rather, it extracts and analyzes interaction data and, then, it groups such data based on factors like geographical location and related cultural background. This study adopts known models of national culture and relates them to social interactions using a large dataset mined from an online community of practice. The results show interesting deviations from the literature, which may be limited to the specific community of practice (programmers sharing coding knowledge) or may guide the design of open innovation systems that support knowledge sharing. This paper presents the first step on why and how to conduct such studies and suggests open questions for future study

A Tale of Two Virtual Communities: A comparative analysis of culture and discourse in two online programming communities

Software programming is increasingly becoming a collaborative and community driven effort, with online discussions becoming vital resources for learning and knowledge sharing. This study explores the differences in the discourse patterns of two popular online programming communities and provides insights into the type of community practices and learning outcomes these collectives support and scaffold. A three step content analysis framework is presented that employs a mixture of automated text processing techniques and qualitative methods on a representative sample of 8639 and 6126 contributions from Stack Overflow and r/Askprogramming respectively. Results indicate differences between communities in the scope of topics and the nature of responses provided. While r/Askprogramming has a more community centric, interpersonal approach and provides a space for sharing and supporting needs beyond knowledge sharing and factual learning, Stack Overflow takes a more task focused, knowledge centric approach. These findings suggest key normative structures that regulate patterns of collaboration and deliberation, which may have long term design implications for structuring and sustaining informal learning initiatives that nurture and promote technical skill development and enhancement

Robust Systems of Cooperation

This dissertation examines the robustness of systems of cooperation—the ability to maintain levels of cooperation in the presence of a potentially disruptive force. I examine rankings as a potentially disruptive force that is commonplace in organizations. A ranking is the ordering of individuals according to their performance on a specific dimension. Systems of cooperation often operate in contexts that feature rankings (e.g., the ride-sharing company Uber uses a “rank and yank” performance evaluation system, yet still expects cooperation on complex cooperative coding tasks) and some explicitly use rankings to motivate cooperative contributions toward a collective goal (e.g., the character improvement App “Peeple” consists of members’ public evaluations of each other’s character and uses a public “positivity rating” to motivate members to maintain a more collegial environment). Yet, a growing body of research is highlighting potential downsides to rankings that could undermine the maintenance of systems of cooperation. This research suggests that rankings may unexpectedly introduce new dynamics into a system of cooperation that drive actors toward uncooperative behaviors and undermine the system as a whole. This dissertation aims to address this tension by exploring how systems of cooperation interact with rankings. Specifically, it explores how rankings can both enrich and perturb a system of cooperation and how systems can achieve robust cooperation in the presence of rankings. Chapter 1 introduces the dual role of rankings for systems of cooperation, reflects on the importance of identifying characteristics that make these systems robust, and discusses how the changing nature of work creates a new urgency for understanding how rankings affect cooperation. This introductory chapter is followed by two empirical chapters that examine distinct pieces of the puzzle for how rankings affect the maintenance of cooperation over time. Chapter 2 examines how the introduction of a performance ranking affects established systems of cooperation. Using a between-groups, no-deception experimental design that includes 74 groups, 594 participants, and over 11,000 cooperation decisions, it examines 1) whether the self-sustaining properties of systems of cooperation are naturally able to overcome the potentially disruptive effects of rankings, and 2) in the case of disruption how managers may be able to restore cooperation in the presence of rankings—making these systems of cooperation more robust. Chapter 3 examines an online community that explicitly uses a ranking to promote cooperation. Using over 1.2 million observations of members’ weekly behaviors, this chapter examines how potential losses and gains in rank inspire individuals to perform both cooperative and uncooperative behaviors and explores how the system-level implications of these behaviors may affect the robustness of systems of cooperation. Chapter 4 concludes the dissertation by synthesizing findings from the empirical chapters, discussing their joint implications for building robust systems of cooperation, and detailing areas of future research.PHDBusiness AdministrationUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/145900/1/caceves_1.pd

Relationship between Gender and Code Reading Speed in Software Development

Recently, workforce shortage has become a popular issue in information technology (IT). One solution to increasing the workforce supply is to increase the number of female IT professionals. This is because there is gender imbalance in information technology area. To accomplish this, it is important to suppress the influence of biases, such as the belief that men are more suited for careers in science and technology than women, and to increase the choice of careers available to female professionals. To help suppress the influence of gender bias, we analyzed the relationship between gender and code reading speed in the field of software development. Certain source codes require developers to use substantial memory to properly understand them, such as those with many variables that frequently change values. Several studies have indicated that the performance of memory differs in males and females. To test the veracity of this claim, we analyzed the influence of gender on code-reading speed through an experiment. Pursuant to this, we prepared four programs that required varied amounts of memory to properly understand them. Then, we measured the time required by each of the 17 male and 16 female subjects (33 subjects in total) to comprehend the different programs. The results suggest that there is no explicit difference between male and female subjects in this regard, even in the case of programs that require high memory capacities for proper understanding.Comment: Japanese letter version is available at: https://search.ieice.org/bin/summary.php?id=j104-d_5_521&category=D&year=2021&lang=J&abst