Abstract Members of cooperative groups can work together more effectively if they develop a shared classification schema, but distributed groups face barriers to doing so. To better understand how classifications and classification practices can emerge and support the work of distributed groups, we review the literature on folksonomies (a kind of shared classification schema) in crowdsourcing projects (one type of distributed work). The review yields three potentially productive tensions associated with the development of folksonomies in crowdsourcing projects. First, projects must establish who has the authority to decide on adopted terminology and with what consequences. Second, there can be tension if people who tag objects have different interests in tagging than those who use the tags to search for content. Finally, projects must decide when to intervene to maintain a balance between a stable vocabulary and the ability of the project to accommodate ongoing changes. We illustrate these tensions by comparing how they are handled in the photo-sharing site Flickr, the story-sharing site Archive of Our Own (AO3), the internet culture classification site Know Your Meme, and the citizen science project Gravity Spy. The comparison suggests guidelines for project managers regarding the identified tensions.

We explore patterns of interaction with different learning resources (e.g., forums) to predict learning outcomes in an online citizen science project called Gravity Spy. To explore how volunteers engage with and benefit from these resources, we categorize them based on Sørensen's three forms of presence in learning environments: authority-subject, agent-centered, and communal presence. Methodologically, we apply sequence analysis to traces of volunteer interactions with the project to identify engagement patterns with these resources that predict learning. Our interpretation of these patterns is augmented by insights gleaned from interviews with volunteers about their work and use of learning resources. We find that early in the project, volunteers have only a simple task to learn, and completing that task is most predictive of their learning. At more advanced levels, when tasks become more complex, discussions with other volunteers become increasingly important, and interaction patterns become more varied. Viewing learning as a series of routines allows us to articulate precisely how and in what context learning occurs. We conclude by discussing the implications of these findings for designing citizen science projects that promote learning.

Abstract Artificial intelligence (AI) reconfigures work and organization, while work and organization shape AI. In this special issue, we explore these mutual transformations and how they play out across industries and occupations. We argue that, to truly appreciate this transformative power, the use of AI should be understood in relation to key dimensions of the work context. In this editorial, we discuss the sociotechnical dynamics of AI implementation, the research landscape of AI in the context of work, and key contextual factors on the macro‐ and micro‐level that help understand the AI‐work nexus. We then provide directions for future research at the intersection of work and AI.

Abstract The use of intelligent machines—digital technologies that feature data‐driven forms of customization, learning, and autonomous action—is rapidly growing and will continue to impact many industries and domains. This is consequential for communities of researchers, educators, and practitioners concerned with studying, supporting, and educating information professionals. In the face of new developments in artificial intelligence (AI), the research community faces 3 questions: (a) How is AI becoming part of the world of work? (b) How is the world of work becoming part of AI? and (c) How can the information community help address this topic of Work in the Age of Intelligent Machines (WAIM)? This opinion piece considers these 3 questions by drawing on discussion from an engaging 2019 iConference workshop organized by the NSF supported WAIM research coordination network (note: https://waim.network ).

In this paper, we explore how sociotechnical systems support and impede the identity performances and identity expression of communities that have experienced a long history of colonialism, where colonization is the practice through which a foreign power reshapes the social structures and systems of other societies. We conducted a trace ethnography among members of a specific digital platform-Bengali Quora (BnQuora). BnQuora is part of the question and answer (Q&A) platform Quora, where people with this particular ethnolinguistic identity come together to engage in conversations about their identities; identities which were shaped through a long history of colonization in the Global South. In drawing on a conceptual framework that brings together identity performativity, governance, content moderation, and surveillance, we find that the sociotechnical mechanisms of governance that mediate people's performances on the BnQuora platform give rise to a kind of platform identity-certain identities are privileged while others are pushed to the margins based on linguistic practices, nationalities, and religious affiliations. We illustrate this through the themes of moderators as prison guards, collective surveillance as enforcing a majority identity, algorithmic coloniality, and staging as self-imprisonment. Finally, we discuss the ways in which governance shapes a platform's identity and can create, strengthen, and reinforce coloniality.

Peer production projects involve people in many tasks, from editing articles to analyzing datasets. To facilitate mastery of these practices, projects offer a number of learning resources, ranging from project-defined FAQsto individually-oriented search tools and communal discussion boards. However, it is not clear which project resources best support participant learning, overall and at different stages of engagement. We draw onSørensen's framework of forms of presence to distinguish three types of engagement with learning resources:authoritative, agent-centered and communal. We assigned resources from the Gravity Spy citizen-science into these three categories and analyzed trace data recording interactions with resources using a mixed-effects logistic regression with volunteer performance as an outcome variable. The findings suggest that engagement with authoritative resources (e.g., those constructed by project organizers) facilitates performance initially. However, as tasks become more difficult, volunteers seek and benefit from engagement with their own agent-centered resources and community-generated resources. These findings suggest a broader scope for the design of learning resources for peer production

Virtual collaborations bring together people who must work together despite having varied access to and understanding of the work at hand. In many cases, the collaborations are technology supported, meaning that the work is done through shared documents. We develop a framework articulating the characteristics of documents supporting collaborators with access to asymmetric knowledge versus those with access to symmetric knowledge. Drawing on theories about document genre, boundary objects, and provenance, we hypothesize that documents supporting asymmetric collaborators are likely to articulate or prescribe their own (a) purpose, (b) context of use, (c) content and form, and (d) provenance in greater detail than documents supporting symmetric collaborators. We explore these hypotheses through content analysis of documents and instructions for documents from a variety of free/libre open‐source projects (FLOSS). We present findings consistent with the hypotheses developed as well as results extending beyond our theory‐derived assumptions. When participants have access to the same knowledge, the study suggests that prescriptions about the content of documents become less important compared with prescriptions about the context, provenance, and process of work. The study contributes with a dynamic perspective on communicative practices that consider an often‐uneven distribution of knowledge in virtual collaborations.

Researchers studying user behaviors in online communities often conduct analyses of user interaction data recorded in system logs e.g., an edit in Wikipedia. Such analysis relies on collating interactions by a unique identifier such as a user ID. However, if users can contribute without being logged-in (i.e., anonymously) analysis of interaction data omit part of a user's experience. Problematically, anonymous traces are unlikely to be randomly distributed, so their omission can change statistical conclusions, with implications for both research and practice. To understand the impacts on conclusions of leaving out anonymous traces, we conducted an analysis of system logs from two online citizen science projects. Attributing anonymous traces with user IDs, we found that (1) many users contribute anonymously, though with varied patterns; and (2) attributing anonymous traces diminishes empirical evidence used to support theory and change the results of system algorithms. These results suggest anonymous traces have implications for research on user behaviors and the practices associated with using such data to tailor user experiences in online communities.

Research on newcomer roles in peer production sites (e.g., Wikipedia) is characterized by a broad and relatively well articulated set of functionally and culturally recognizable roles. But not all communities come with well-defined roles that newcomers can aspire to occupy. The present study explores activity clusters newcomers create when faced with few recognizable roles to fill and limited access to other participants' work that serves as an exemplar. Drawing on a mixed method research design, we present findings from an analysis of 1,687 newcomers' sessions in an online citizen science project. Our analysis revealed three major findings: (1) newcomers' activities exists across six session types; (2) newcomers toggle between light work sessions and more involved types of production or community engagement; (3) high-level contributors contribute large volumes of work but comment very little and another group contributes large volumes of comments, but works very little. The former group draws heavily on posts contributed by the latter group. Identifying shifts and regularities in contribution facilitate improved mechanisms for engaging participants and for the design of online citizen science communities.

In this paper, we describe the results of an online field experiment examining the impacts of messaging about task novelty on the volume of volunteers' contributions to an online citizen science project. Encouraging volunteers to provide a little more content as they work is an attractive strategy to increase the community's output. Prior research found that an important motivation for participation in online citizen science is the wonder of being the first person to observe a particular image. To appeal to this motivation, a pop-up message was added to an online citizen science project that alerted volunteers when they were the first to annotate a particular image. Our analysis reveals that new volunteers who saw these messages increased the volume of annotations they contributed. The results of our study suggest an additional strategy to increase the amount of work volunteers contribute to online communities and citizen science projects specifically.

Making visible the process of user participation in online crowdsourced initiatives has been shown to help new users understand the norms of participation [2]. However, in many settings, participants lack full access to others' work. Merging the theory of legitimate peripheral participation [18] with Erickson and Kellogg's theory of social translucence [10, 11, 16] we introduce the concept of practice proxies: traces of user participation in online environments that act as resources to orient newcomers towards the norms of practice. Through a combination of virtual [14] and trace ethnography [12] we explore how new users in two online citizen science projects engage with these traces of practice as a way of compensating for a lack of access to the process of the work itself. Our findings suggest that newcomers seek out practice proxies in the social features of the projects that highlight contextualized and specific characteristics of primary work practice.

Contemporary cyberinfrastructure (CI) seem poorly developed to meet the distributed work practices of social scientists. We draw from the literatures of science studies and e-science practices to advance a document-centered articulation of social scientists' distributed work practices. We report on a pilot study to provide some insights into CI needs for these scholars. This study relied on a mixed-methodological approach involving the mapping of digital and physical documents, automated tracking of desktop and online repositories, participant-generated images of physical documents and desktop, behavioral queries, along with interviews and participant observation. Findings suggest a document perspective provides insight into the distributed work practices and CI uses of social scientists.