Journalists are routinely challenged with monitoring vast information environments in order to identify what is newsworthy and of interest to report to a wider audience. In a process referred to as computational news discovery, alerts and leads based on data-driven algorithmic analysis can orient journalists' attention to events, documents, or anomalous patterns in data that are more likely to be newsworthy. In this paper we prototype one such news discovery tool, Algorithm Tips, which we designed to help journalists find newsworthy leads about algorithmic decision-making systems used across all levels of U.S. government. The tool incorporates algorithmic, crowdsourced, and expert evaluations into an integrated interface designed to support users in making editorial decisions about which news leads to pursue. We then present an evaluation of our prototype based on an extended deployment with eight professional journalists. Our findings offer insights into journalistic practices that are enabled and transformed by such news discovery tools, and suggest opportunities for improving computational news discovery tool designs to better support those practices.
https://doi.org/10.1145/3479550
Data science practitioners face the challenge of continually honing their skills such as data wrangling and visualization. As data scientists seek online spaces to network, learn and share resources with one another, each individual has to employ their own ad-hoc strategy to practice their data science skills. Given these disjointed efforts, it is crucial to ask: how can we build an inclusive, welcoming online community of practice that unites data scientists in their collective efforts to become experts? Daily hashtags on Twitter are used on specific days and have shown promise in forming a community of practice (CoP) in social networking sites like Twitter, but how do they benefit the community and its members? To understand how daily hashtags benefit data scientists and form an online CoP, we conducted a qualitative study on #TidyTuesday---a daily hashtag project for data scientists using R---using the framework of CoP as a lens for analysis. We conducted semi-structured interviews with 26 participants and uncovered motivations behind their participation in #TidyTuesday, how the project benefited them, and how it cultivated an online CoP. Our findings contribute to the CSCW research on community of practices by providing design trade-offs of using daily hashtags on Twitter, and guidelines on growing and sustaining an online community of practice for data scientists.
https://doi.org/10.1145/3449126
Music therapists provide critical, evidence-based care to a diverse range of clients. However, despite their active role in empowering individuals affected by disability, stigma, grief, and trauma, music therapists remain understudied by the HCI community. We present the results of a mixed methods study of 10 interviewees and 20 survey respondents in the U.S., all of whom are practicing music therapists. Our results show that music therapists engage in technology-aided practices such as making personalized connections with clients, assisting in identity formation, encouraging musicking (music-making), and preserving legacies. Results also show that music therapists face key challenges such as environmental, societal, and financial constraints, including high workload, lack of awareness of the value of music therapy among the general community, and limited access to secure technologies for remote client care. In light of these challenges, we present a set of design implications for creating future technologies for music therapists. This work diverges from previous studies on music therapy technologies, which focus largely on interventions with music therapy clients, by highlighting the often-neglected perspectives from music therapists.
https://doi.org/10.1145/3449107
While surgical videos are valuable support material for activities around surgery, their summarization demands great amounts of time from surgeons, leading to very few videos being produced. We study the practices around surgical video to motivate and inform the design of dedicated tools. Through interviews and observations in a field study, we find that (1) video summaries provide an important support for surgery, being used for self-improvement, education, discussing cases, scientific publications, patient communication and as legal resources; (2) video summarization follows a process, hindered by the loss of knowledge that originates during recording; and (3) surgeons develop ad-hoc strategies to articulate coordination. These strategies involve using the video for articulation work, making it both the coordination artifact and the field of work. We discuss ways in which tools can facilitate capturing knowledge in live action using this strategy.
https://doi.org/10.1145/3449214
The development of AI applications is a multidisciplinary effort, involving multiple roles collaborating with the AI developers, an umbrella term we use to include data scientists and other AI-adjacent roles on the same team. During these collaborations, there is a knowledge mismatch between AI developers, who are skilled in data science, and external stakeholders who are typically not. This difference leads to communication gaps, and the onus falls on AI developers to explain data science concepts to their collaborators. In this paper, we report on a study including analyses of both interviews with AI developers and artifacts they produced for communication. Using the analytic lens of shared mental models, we report on the types of communication gaps that AI developers face, how AI developers communicate across disciplinary and organizational boundaries, and how they simultaneously manage issues regarding trust and expectations.
https://doi.org/10.1145/3449205
The construct of “situational awareness” (SA) has a rich and productive history within both academic literature and practice. Situational awareness as a technical term has its earliest roots in formative human factors research in service of military and flight applications. However, its value as a construct in other domains, particularly those having to do with rapid sensemaking in safety-sensitive conditions, has led to a broader applied and theoretical interest over the past few decades. As a discipline, CSCW has been relatively less engaged with this concept, but has empirical and theoretical tools that will be valuable to its study. To bring CSCW more fully into the conversation, we present a description of how operators in a city department of transportation’s transportation management center (TMC) develop and maintain situational awareness for themselves and the key recipients of their critical information outputs. We identify some of the schemas operators must develop in order to effectively construct situational awareness and dynamically articulate common fields of work, and the social collaborative practices they engage in to support that awareness. Implications for design and further research are proposed.
https://doi.org/10.1145/3449128
Investigators in fields such as journalism and law enforcement have long sought the public’s help with investigations. New technologies have also allowed amateur sleuths to lead their own crowdsourced investigations (CIs), that have traditionally only been the purview of expert investigators. These CIs have been faced with mixed results. Through an ethnographic study at a four-day long co-located event with over 250 attendees, we examine the human infrastructure responsible for enabling the success of an expert-led CI. We find that the experts enabled attendees to generate useful leads; the attendees formed a community around the event; and the victims’ families felt supported. However, the co-located setting, legal structures, and emergent social norms impacted collaborative work practice. We also surface three important tensions for CIs to consider and provide design recommendations to manage these tensions.
https://doi.org/10.1145/3449192
The goal of this study was to examine the work practices of behavioral health professionals with a view towards designing interactive systems to support their work. We conducted a qualitative workplace study, including in situ observations and semi-structured interviews, in a multidisciplinary clinic treating pediatric feeding disorders. This paper contributes a detailed characterization of clinicians' work practices and conducts a comparative analysis of three types of work: treatment, record management, and preparation work. We found that clinicians have a preference for taxing over tedious work. For example, they experience real-time data collection as more taxing but less tedious than retroactive data entry. Design efforts should balance the tension between addressing the taxing (data collection during meals) versus the tedious (manually entering data into spreadsheets). Although addressing the taxing improves within-routine efficiency, addressing the tedious improves overall morale. Further, we hypothesize that there is a rewarding or unrewarding quality to work that is dictated in part by its social, temporal, and clinical characteristics. We discuss conceptual and design implications for supporting clinical work, and highlight considerations unique to behavioral health.
https://doi.org/10.1145/3476043