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Benjamin Mako Hill

Publications and source records attributed to Benjamin Mako Hill.

34 records · Page 2Linked to original sources

Qualities of Quality: A Tertiary Review of Software Quality Measurement Research

This paper presents a tertiary review of software quality measurement research. To conduct this review, we examined an initial dataset of 7,811 articles and found 75 relevant and high-quality secondary analyses of software quality research. Synthesizing this body of work, we offer an overview of perspectives, measurement approaches, and trends. We identify five distinct perspectives that conceptualize quality as heuristic, as maintainability, as a holistic concept, as structural features of software, and as dependability. We also identify three key challenges. First, we find widespread evidence of validity questions with common measures. Second, we observe the application of machine learning methods without adequate evaluation. Third, we observe the use of aging datasets. Finally, from these observations, we sketch a path toward a theoretical framework that will allow software engineering researchers to systematically confront these weaknesses while remaining grounded in the experiences of developers and the real world in which code is ultimately deployed.

cs.SE↗

Underproduction: An Approach for Measuring Risk in Open Source Software

The widespread adoption of Free/Libre and Open Source Software (FLOSS) means that the ongoing maintenance of many widely used software components relies on the collaborative effort of volunteers who set their own priorities and choose their own tasks. We argue that this has created a new form of risk that we call 'underproduction' which occurs when the supply of software engineering labor becomes out of alignment with the demand of people who rely on the software produced. We present a conceptual framework for identifying relative underproduction in software as well as a statistical method for applying our framework to a comprehensive dataset from the Debian GNU/Linux distribution that includes 21,902 source packages and the full history of 461,656 bugs. We draw on this application to present two experiments: (1) a demonstration of how our technique can be used to identify at-risk software packages in a large FLOSS repository and (2) a validation of these results using an alternate indicator of package risk. Our analysis demonstrates both the utility of our approach and reveals the existence of widespread underproduction in a range of widely-installed software components in Debian.

cs.SE↗

Designing for Critical Algorithmic Literacies

As pervasive data collection and powerful algorithms increasingly shape children's experience of the world and each other, their ability to interrogate computational algorithms has become crucially important. A growing body of work has attempted to articulate a set of "literacies" to describe the intellectual tools that children can use to understand, interrogate, and critique the algorithmic systems that shape their lives. Unfortunately, because many algorithms are invisible, only a small number of children develop the literacies required to critique these systems. How might designers support the development of critical algorithmic literacies? Based on our experience designing two data programming systems, we present four design principles that we argue can help children develop literacies that allow them to understand not only how algorithms work, but also to critique and question them.

cs.HC↗

How individual behaviors drive inequality in online community sizes: an agent-based simulation

Why are online community sizes so extremely unequal? Most answers to this question have pointed to general mathematical processes drawn from physics like cumulative advantage. These explanations provide little insight into specific social dynamics or decisions that individuals make when joining and leaving communities. In addition, explanations in terms of cumulative advantage do not draw from the enormous body of social computing research that studies individual behavior. Our work bridges this divide by testing whether two influential social mechanisms used to explain community joining can also explain the distribution of community sizes. Using agent-based simulations, we evaluate how well individual-level processes of social exposure and decisions based on individual expected benefits reproduce empirical community size data from Reddit. Our simulations contribute to social computing theory by providing evidence that both processes together---but neither alone---generate realistic distributions of community sizes. Our results also illustrate the potential value of agent-based simulation to online community researchers to both evaluate and bridge individual and group-level theories.

cs.CY↗

Are anonymity-seekers just like everybody else? An analysis of contributions to Wikipedia from Tor

User-generated content sites routinely block contributions from users of privacy-enhancing proxies like Tor because of a perception that proxies are a source of vandalism, spam, and abuse. Although these blocks might be effective, collateral damage in the form of unrealized valuable contributions from anonymity seekers is invisible. One of the largest and most important user-generated content sites, Wikipedia, has attempted to block contributions from Tor users since as early as 2005. We demonstrate that these blocks have been imperfect and that thousands of attempts to edit on Wikipedia through Tor have been successful. We draw upon several data sources and analytical techniques to measure and describe the history of Tor editing on Wikipedia over time and to compare contributions from Tor users to those from other groups of Wikipedia users. Our analysis suggests that although Tor users who slip through Wikipedia's ban contribute content that is more likely to be reverted and to revert others, their contributions are otherwise similar in quality to those from other unregistered participants and to the initial contributions of registered users.

cs.SI↗

A Forensic Qualitative Analysis of Contributions to Wikipedia from Anonymity Seeking Users

By choice or by necessity, some contributors to commons-based peer production sites use privacy-protecting services to remain anonymous. As anonymity seekers, users of the Tor network have been cast both as ill-intentioned vandals and as vulnerable populations concerned with their privacy. In this study, we use a dataset drawn from a corpus of Tor edits to Wikipedia to uncover the character of Tor users' contributions. We build in-depth narrative descriptions of Tor users' actions and conduct a thematic analysis that places their editing activity into seven broad groups. We find that although their use of a privacy-protecting service marks them as unusual within Wikipedia, the character of many Tor users' contributions is in line with the expectations and norms of Wikipedia. However, our themes point to several important places where lack of trust promotes disorder, and to contributions where risks to contributors, service providers, and communities are unaligned.

cs.CY↗

A longitudinal dataset of five years of public activity in the Scratch online community

Scratch is a programming environment and an online community where young people can create, share, learn, and communicate. In collaboration with the Scratch Team at MIT, we created a longitudinal dataset of public activity in the Scratch online community during its first five years (2007-2012). The dataset comprises 32 tables with information on more than 1 million Scratch users, nearly 2 million Scratch projects, more than 10 million comments, more than 30 million visits to Scratch projects, and more. To help researchers understand this dataset, and to establish the validity of the data, we also include the source code of every version of the software that operated the website, as well as the software used to generate this dataset. We believe this is the largest and most comprehensive downloadable dataset of youth programming artifacts and communication.

cs.CY↗

Scratch Community Blocks: Supporting Children as Data Scientists

In this paper, we present Scratch Community Blocks, a new system that enables children to programmatically access, analyze, and visualize data about their participation in Scratch, an online community for learning computer programming. At its core, our approach involves a shift in who analyzes data: from adult data scientists to young learners themselves. We first introduce the goals and design of the system and then demonstrate it by describing example projects that illustrate its functionality. Next, we show through a series of case studies how the system engages children in not only representing data and answering questions with data but also in self-reflection about their own learning and participation.

cs.HC↗

Surviving an "Eternal September" - How an Online Community Managed a Surge of Newcomers

We present a qualitative analysis of interviews with participants in the NoSleep community within Reddit where millions of fans and writers of horror fiction congregate. We explore how the community handled a massive, sudden, and sustained increase in new members. Although existing theory and stories like Usenet's infamous "Eternal September" suggest that large influxes of newcomers can hurt online communities, our interviews suggest that NoSleep survived without major incident. We propose that three features of NoSleep allowed it to manage the rapid influx of newcomers gracefully: (1) an active and well-coordinated group of administrators, (2) a shared sense of community which facilitated community moderation, and (3) technological systems that mitigated norm violations. We also point to several important trade-offs and limitations.

cs.HC↗

Remixing as a Pathway to Computational Thinking

Theorists and advocates of "remixing" have suggested that appropriation can act as a pathway for learning. We test this theory quantitatively using data from more than 2.4 million multimedia programming projects shared by more than 1 million users in the Scratch online community. First, we show that users who remix more often have larger repertoires of programming commands even after controlling for the numbers of projects and amount of code shared. Second, we show that exposure to computational thinking concepts through remixing is associated with increased likelihood of using those concepts. Our results support theories that young people learn through remixing, and have important implications for designers of social computing systems.

cs.CY↗

Responses to remixing on a social media sharing website

In this paper we describe the ways participants of the Scratch online community, primarily young people, engage in remixing of each others' shared animations, games, and interactive projects. In particular, we try to answer the following questions: How do users respond to remixing in a social media environment where remixing is explicitly permitted? What qualities of originators and their projects correspond to a higher likelihood of plagiarism accusations? Is there a connection between plagiarism complaints and similarities between a remix and the work it is based on? Our findings indicate that users have a very wide range of reactions to remixing and that as many users react positively as accuse remixers of plagiarism. We test several hypotheses that might explain the high number of plagiarism accusations related to original project complexity, cumulative remixing, originators' integration into remixing practice, and remixee-remixer project similarity, and find support for the first and last explanations.

cs.HC↗

Computers Can't Give Credit: How Automatic Attribution Falls Short in an Online Remixing Community

In this paper, we explore the role that attribution plays in shaping user reactions to content reuse, or remixing, in a large user-generated content community. We present two studies using data from the Scratch online community -- a social media platform where hundreds of thousands of young people share and remix animations and video games. First, we present a quantitative analysis that examines the effects of a technological design intervention introducing automated attribution of remixes on users' reactions to being remixed. We compare this analysis to a parallel examination of "manual" credit-giving. Second, we present a qualitative analysis of twelve in-depth, semi-structured, interviews with Scratch participants on the subject of remixing and attribution. Results from both studies suggest that automatic attribution done by technological systems (i.e., the listing of names of contributors) plays a role that is distinct from, and less valuable than, credit which may superficially involve identical information but takes on new meaning when it is given by a human remixer. We discuss the implications of these findings for the designers of online communities and social media platforms.

cs.HC↗

The Cost of Collaboration for Code and Art: Evidence from a Remixing Community

In this paper, we use evidence from a remixing community to evaluate two pieces of common wisdom about collaboration. First, we test the theory that jointly produced works tend to be of higher quality than individually authored products. Second, we test the theory that collaboration improves the quality of functional works like code, but that it works less well for artistic works like images and sounds. We use data from Scratch, a large online community where hundreds of thousands of young users share and remix millions of animations and interactive games. Using peer-ratings as a measure of quality, we estimate a series of fitted regression models and find that collaborative Scratch projects tend to receive ratings that are lower than individually authored works. We also find that code-intensive collaborations are rated higher than media-intensive efforts. We conclude by discussing the limitations and implications of these findings.

cs.CY↗

The Remixing Dilemma: The Trade-off Between Generativity and Originality

In this paper we argue that there is a trade-off between generativity and originality in online communities that support open collaboration. We build on foundational theoretical work in peer production to formulate and test a series of hypotheses suggesting that the generativity of creative works is associated with moderate complexity, prominent authors, and cumulativeness. We also formulate and test three hypotheses that these qualities are associated with decreased originality in resulting derivatives. Our analysis uses a rich data set from the Scratch Online Community --a large web-site where young people openly share and remix animations and video games. We discuss the implications of this trade-off for the design of peer production systems that support amateur creativity.

cs.CY↗

WeDo: Exploring Participatory, End-To-End Collective Action

Many celebrate the Internet's ability to connect individuals and facilitate collective action toward a common goal. While numerous systems have been designed to support particular aspects of collective action, few systems support participatory, end-to-end collective action in which a crowd or community identifies opportunities, formulates goals, brainstorms ideas, develops plans, mobilizes, and takes action. To explore the possibilities and barriers in supporting such interactions, we have developed WeDo, a system aimed at promoting simple forms of participatory, end-to-end collective action. Pilot deployments of WeDo illustrate that sociotechnical systems can support automated transitions through different phases of end-to-end collective action, but that challenges, such as the elicitation of leadership and the accommodation of existing group norms, remain.

cs.CY↗

Laboratories of Oligarchy? How the Iron Law Extends to Peer Production

Peer production projects like Wikipedia have inspired voluntary associations, collectives, social movements, and scholars to embrace open online collaboration as a model of democratic organization. However, many peer production projects exhibit entrenched leadership and deep inequalities, suggesting that they may not fulfill democratic ideals. Instead, peer production projects may conform to Robert Michels' "iron law of oligarchy," which proposes that democratic membership organizations become increasingly oligarchic as they grow. Using exhaustive data of internal processes from a sample of 683 wikis, we construct empirical measures of participation and test for increases in oligarchy associated with growth. In contrast to previous studies, we find support for Michels' iron law and conclude that peer production entails oligarchic organizational forms.

cs.CY↗