bluuebunny/crossref_metadata_2025 huggingface dataset:
Artistic glyph image synthesis via one-stage few-shot learning
Authors: Gao Yue , Guo Yuan , Lian Zhouhui , Tang Yingmin , Xiao Jianguo
Published: November 2019

Automatic generation of artistic glyph images is a challenging task that attracts many research interests. Previous methods either are specifically designed for shape synthesis or focus on texture transfer. In this paper, we propose a novel model, AGIS-Net, to transfer both shape and texture styles in one-stage with only a few stylized samples. To achieve this goal, we first disentangle the representations for content and style by using two encoders, ensuring the multi-content and multi-style generation. Then we utilize two collaboratively working decoders to generate the glyph shape image and its texture image simultaneously. In addition, we introduce a local texture refinement loss to further improve the quality of the synthesized textures. In this manner, our one-stage model is much more efficient and effective than other multi-stage stacked methods. We also propose a large-scale dataset with Chinese glyph images in various shape and texture styles, rendered from 35 professional-designed artistic fonts with 7,326 characters and 2,460 synthetic artistic fonts with 639 characters, to validate the effectiveness and extendability of our method. Extensive experiments on both English and Chinese artistic glyph image datasets demonstrate the superiority of our model in generating high-quality stylized glyph images against other state-of-the-art methods.
X-CAD
Authors: Hafner Christian , Schumacher Christian , Knoop Espen , Auzinger Thomas , Bickel Bernd , Bächer Moritz
Published: November 2019

We propose a novel generic shape optimization method for CAD models based on the eXtended Finite Element Method (XFEM). Our method works directly on the intersection between the model and a regular simulation grid, without the need to mesh or remesh, thus removing a bottleneck of classical shape optimization strategies. This is made possible by a novel hierarchical integration scheme that accurately integrates finite element quantities with sub-element precision. For optimization, we efficiently compute analytical shape derivatives of the entire framework, from model intersection to integration rule generation and XFEM simulation. Moreover, we describe a differentiable projection of shape parameters onto a constraint manifold spanned by user-specified shape preservation, consistency, and manufacturability constraints. We demonstrate the utility of our approach by optimizing mass distribution, strength-to-weight ratio, and inverse elastic shape design objectives directly on parameterized 3D CAD models.
The Perpetual Work Life of Crowdworkers
Authors: Williams Alex C. , Mark Gloria , Milland Kristy , Lank Edward , Law Edith
Published: November 2019

Crowdworkers regularly support their work with scripts, extensions, and software to enhance their productivity. Despite their evident significance, little is understood regarding how these tools affect crowdworkers' quality of life and work. In this study, we report findings from an interview study (N=21) aimed at exploring the tooling practices used by full-time crowdworkers on Amazon Mechanical Turk. Our interview data suggests that the tooling utilized by crowdworkers (1) strongly contributes to the fragmentation of microwork by enabling task switching and multitasking behavior; (2) promotes the fragmentation of crowdworkers' work-life boundaries by relying on tooling that encourages a 'work-anywhere' attitude; and (3) aids the fragmentation of social ties within worker communities through limited tooling access. Our findings have implications for building systems that unify crowdworkers' work practice in support of their productivity and well-being.
Automatically Analyzing Brainstorming Language Behavior with Meeter
Authors: Huber Bernd , Shieber Stuart , Gajos Krzysztof Z.
Published: November 2019

Language both influences and indicates group behavior, and we need tools that let us study the content of what is communicated. While one could annotate these spoken dialogue acts by hand, this is a tedious, not scalable process. We present Meeter, a tool for automatically detecting information sharing, shared understanding, word counts, and group activation in spoken interactions. The contribution of our work is two-fold: (1) We validated the tool by showing that the measures computed by Meeter align with human-generated labels, and (2) we demonstrated the value of Meeter as a research tool by quantifying aspects of group behavior using those measures and deriving novel findings from that. Our tool is valuable for researchers conducting group science, as well as those designing groupware systems.
Towards Successful Knowledge Integration in Online Collaboration
Authors: Osinski Meike , Rummel Nikol
Published: November 2019

Successful knowledge integration, that is, systematic synthesis of unshared information, is key to suc-cess, but at the same time a challenging venture for teams with distributed knowledge collaborating online. For example, teams with heterogeneous knowledge often have only vague or even wrong ideas about who knows what. This situation is further complicated if the collaboration partners do not know each other and merely communicate online. Previous research has found meta-knowledge, that is, knowledge about one's own and the partner's knowledge areas, to be a promising but not yet sufficient-ly investigated approach to promote knowledge integration. With our experimental study we aimed to address this desideratum of research on the role of meta-knowledge in net-based collaborations. We "simulated" a chat-based collaboration between partners with heterogeneous knowledge by assigning specific information to students collaborating in dyads on a Hidden Profile task. To arrive at the correct joint solution for this task, collaborating partners had to pool their shared, but more importantly their unshared information. We compared two conditions: In the experimental condition meta-knowledge was promoted by providing the collaboration partners with self-presentations of each other's roles, which pointed to their unique fields of knowledge, while participants in the control condition did not receive this information. Results suggest a positive impact of the meta-knowledge manipulation on two key factors of collaboration: knowledge integration and construction of a transactive memory system (TMS).
The Dynamics of Peer-Produced Political Information During the 2016 U.S. Presidential Campaign
Authors: Keegan Brian C.
Published: November 2019

Wikipedia plays a crucial role for online information seeking and its editors have a remarkable capacity to rapidly revise its content in response to current events. How did the production and consumption of political information on Wikipedia mirror the dynamics of the 2016 U.S. Presidential campaign? Drawing on systems justification theory and methods for measuring the enthusiasm gap among voters, this paper quantitatively analyzes the candidates' biographical and related articles and their editors. Information production and consumption patterns match major events over the course of the campaign, but Trump-related articles show consistently higher levels of engagement than Clinton-related articles. Analysis of the editors' participation and backgrounds show analogous shifts in the composition and durability of the collaborations around each candidate. The implications for using Wikipedia to monitor political engagement are discussed.
How I Learned What a Domain Was
Authors: Ribes David
Published: November 2019

This paper re-traverses the author's investigations across several years as he sought to pin-down the meaning of the in vivo category 'domain'. The paper is a methodological reflection on the grounded theory approach to concept development, with a focus on the technical terms: in vivo category, iteration on the code, and sensitizing category. It is also a substantive theoretical contribution, elaborating the concept of a domain in computing, data and information science, and how it has long served as an organizing principle for developing computational systems. Four tricks of the trade for studying the 'logic of domains' are offered as sensitizing concepts to aid future investigations.
"I think people are powerful"
Authors: Burgess Eleanor R. , Ringland Kathryn E. , Nicholas Jennifer , Knapp Ashley A. , Eschler Jordan , Mohr David C. , Reddy Madhu C.
Published: November 2019

Millions of Americans struggle with depression, a condition characterized by feelings of sadness and motivation loss. To understand how individuals managing depression conceptualize their self-management activities, we conducted visual elicitations and semi-structured interviews with 30 participants managing depression in a large city in the U.S. Midwest. Many depression support tools are focused on the individual user and do not often incorporate social features. However, our analysis showed the key importance of sociality for self-management of depression. We describe how individuals connect with specific others to achieve expected support and how these interactions are mediated through locations and communication channels. We discuss factors influencing participants' sociality including relationship roles and expectations, mood state and communication channels, location and privacy, and culture and society. We broaden our understanding of sociality in CSCW through discussing diffuse sociality (being proximate to others but not interacting directly) as an important activity to support depression self-management.
"My cousin bought the phone for me. I never go to mobile shops."
Authors: Ibtasam Samia , Razaq Lubna , Ayub Maryam , Webster Jennifer R. , Ahmed Syed Ishtiaque , Anderson Richard
Published: November 2019

The intersection of Islam and gender affect technological and social interactions for Muslim women in significant ways and remains an understudied domain for CSCW and related fields. Building on 73 qualitative interviews with low-income women in Punjab, Pakistan, we analyze the complexity of family relationships and the subsequent dynamics of authority around technology uptake and usage by women within non-Western contexts, and, specifically, within the Islamic world. We argue that a Pakistani woman's experience with technology depends on many factors, including gendered roles, generational differences in a family, and wider socio-cultural and religious influences against the backdrop of a culturally conservative and patriarchal society. Our paper highlights the rich family dynamics, including key life events, that transform the roles of both Muslim women and their relatives. Our work is intended to inform scholars, practitioners within development agencies and industry, and other individuals studying technology and development about household dynamics that influence Muslim women's use of technology to encourage them to consider these dynamics during design and implementation processes for technological inclusion.
Speedrunning for Charity
Authors: Sher Stephen Tsung-Han , Su Norman Makoto
Published: November 2019

Games Done Quick (GDQ) is both a week-long video game speedrunning marathon and a successful charity event, raising more than $1.5 million USD in each of its past five events. To understand GDQ's success as an online charity event, we conducted 18 semi-structured interviews with GDQ speedrunners, attendees, hosts, and online viewers, analyzed past donation data, and conducted 72 hours of in-person participant observations at a live GDQ event. We found that central to every GDQ event is "the couch" which reconstructs the environment of a living room. Viewers do not simply donate to support the charity or in response to the technical prowess and ingenuity of speedrunners, but to actively interact with and be part of the couch experience, the ideal social milieu of speedrunning. Building upon previously identified motivations of why viewers donate to online live streamers, our work contributes to understanding how collocated gatherings can reinforce and amplify the cultural and social aspects of online subcultures (even heterogeneous ones) to encourage charitable giving. This opens opportunities for design that evoke a visceral level of engagement with charity events similar to that observed at GDQ.
Moderation Challenges in Voice-based Online Communities on Discord
Authors: Jiang Jialun Aaron , Kiene Charles , Middler Skyler , Brubaker Jed R. , Fiesler Casey
Published: November 2019

Online community moderators are on the front lines of combating problems like hate speech and harassment, but new modes of interaction can introduce unexpected challenges. In this paper, we consider moderation practices and challenges in the context of real-time, voice-based communication through 25 in-depth interviews with moderators on Discord. Our findings suggest that the affordances of voice-based online communities change what it means to moderate content and interactions. Not only are there new ways to break rules that moderators of text-based communities find unfamiliar, such as disruptive noise and voice raiding, but acquiring evidence of rule-breaking behaviors is also more difficult due to the ephemerality of real-time voice. While moderators have developed new moderation strategies, these strategies are limited and often based on hearsay and first impressions, resulting in problems ranging from unsuccessful moderation to false accusations. Based on these findings, we discuss how voice communication complicates current understandings and assumptions about moderation, and outline ways that platform designers and administrators can design technology to facilitate moderation.
Infrastructuring Food Democracy
Authors: Prost Sebastian , Vlachokyriakos Vasilis , Midgley Jane , Heron Graeme , Meziant Kahina , Crivellaro Clara
Published: November 2019

This paper discusses what infrastructuring in participatory design can contribute to processes of food system democratisation. It presents almost two years of engagement with a community-based organisation in a socio-economically deprived neighbourhood in England with the aim of developing a local food hub. It documents how the collaborative work shifted from setting up an infrastructure to ongoing infrastructuring of an enabling environment to grow and sustain social innovation. While the former focused on a technological platform and a business to deliver inclusivity, customer experience, and marketing, the latter focuses on building lasting relationships on three levels: strengthening ties within the community-based organisation, offering social spaces to connect with the local community, and with other organisations by forming coalitions with mutual benefits. We contribute three design opportunities: First, in order to infrastructure the formation of publics around food initiatives, we need to design for relationship building. Second, we point to design implications for ethical aspirations, participation, and system transformation towards a food democracy. Finally, we reflect on the sustainability of infrastructuring and the role of designers to work towards independent infrastructures.
Efficient Elicitation Approaches to Estimate Collective Crowd Answers
Authors: Chung John Joon Young , Song Jean Y. , Kutty Sindhu , Hong Sungsoo (Ray) , Kim Juho , Lasecki Walter S.
Published: November 2019

When crowdsourcing the creation of machine learning datasets, statistical distributions that capture diverse answers can represent ambiguous data better than a single best answer. Unfortunately, collecting distributions is expensive because a large number of responses need to be collected to form a stable distribution. Despite this, the efficient collection of answer distributions-that is, ways to use less human effort to collect estimates of the eventual distribution that would be formed by a large group of responses-is an under-studied topic. In this paper, we demonstrate that this type of estimation is possible and characterize different elicitation approaches to guide the development of future systems. We investigate eight elicitation approaches along two dimensions: annotation granularity and estimation perspective. Annotation granularity is varied by annotating i) a single "best" label, ii) all relevant labels, iii) a ranking of all relevant labels, or iv) real-valued weights for all relevant labels. Estimation perspective is varied by prompting workers to either respond with their own answer or an estimate of the answer(s) that they expect other workers would provide. Our study collected ordinal annotations on the emotional valence of facial images from 1,960 crowd workers and found that, surprisingly, the most fine-grained elicitation methods were not the most accurate, despite workers spending more time to provide answers. Instead, the most efficient approach was to ask workers to choose all relevant classes that others would have selected. This resulted in a 21.4% reduction in the human time required to reach the same performance as the baseline (i.e., selecting a single answer with their own perspective). By analyzing cases in which finer-grained annotations degraded performance, we contribute to a better understanding of the trade-offs between answer elicitation approaches. Our work makes it more tractable to use answer distributions in large-scale tasks such as ML training, and aims to spark future work on techniques that can efficiently estimate answer distributions.
Cross-Cultural Differences in the Use of Online Mental Health Support Forums
Authors: Pendse Sachin R. , Niederhoffer Kate , Sharma Amit
Published: November 2019

Online mental health forums facilitate supportive relationships between peers that transcend national and cultural boundaries. While past work in medical anthropology indicates a central role of cultural identity in how individuals frame their mental well-being and distress, little research has been done to investigate the role of culture in seeking and providing mental health support on online forums. Using data from two mental health forums, we analyze cross-cultural differences in mental health expression between people from different countries. We characterize these differences along three dimensions--identity, language use, and support behavior. Through comparing usage of the platform by individuals from three Asian countries with their counterparts from primarily Western countries, we find that individuals from these less-represented countries mention their own country more often when expressing distress, use fewer clinical language terms, and are more likely to provide support to people from the same country as them, as expected from past work on mental health in these countries. Contrary to past work, however, we find that the use of clinical mental health language is not affected over time by interacting with others in an international forum. While these findings are useful for understanding the role of culture in mental health support, they also have practical design implications for online forums. We find that the three dimensions of cultural differences we analyze are correlated with receiving effective support, and make design recommendations that can improve quality of support for the people in the minority on these forums.
Reliability and Inter-rater Reliability in Qualitative Research
Authors: McDonald Nora , Schoenebeck Sarita , Forte Andrea
Published: November 2019

What does reliability mean for building a grounded theory? What about when writing an auto-ethnography? When is it appropriate to use measures like inter-rater reliability (IRR)? Reliability is a familiar concept in traditional scientific practice, but how, and even whether to establish reliability in qualitative research is an oft-debated question. For researchers in highly interdisciplinary fields like computer-supported cooperative work (CSCW) and human-computer interaction (HCI), the question is particularly complex as collaborators bring diverse epistemologies and training to their research. In this article, we use two approaches to understand reliability in qualitative research. We first investigate and describe local norms in the CSCW and HCI literature, then we combine examples from these findings with guidelines from methods literature to help researchers answer questions like: "should I calculate IRR?" Drawing on a meta-analysis of a representative sample of CSCW and HCI papers from 2016-2018, we find that authors use a variety of approaches to communicate reliability; notably, IRR is rare, occurring in around 1/9 of qualitative papers. We reflect on current practices and propose guidelines for reporting on reliability in qualitative research using IRR as a central example of a form of agreement. The guidelines are designed to generate discussion and orient new CSCW and HCI scholars and reviewers to reliability in qualitative research.
Should We Use an Abstract Comic Form to Persuade?
Authors: Xiao Ziang , Ho Po-Shiun , Wang Xinran , Karahalios Karrie , Sundaram Hari
Published: November 2019

This paper examines the use of the abstract comic form for persuading online charitable donations. Persuading individuals to contribute to charitable causes online is hard and responses to the appeals are typically low; charitable donations share the structure of public goods dilemmas where the rewards are distant and non-exclusive. In this paper, we examine if comics in abstract form are more persuasive than in the plain text form. Drawing on a rich literature on comics, we synthesized a three-panel abstract comic to create our appeal. We conducted a between-subject study with 307 participants from Amazon Mechanical Turk on the use of abstract comic form to appeal for charitable donations. As part of our experimental procedure, we sought to persuade individuals to contribute to a real charity focused on Autism research with monetary costs. We compared the average amount of donation to the charity under three conditions: the plain text message, an abstract comic that includes the plain text, and an abstract comic that additionally includes the social proof. We use Bayesian modeling to analyze the results, motivated by model transparency and its use in small-sized studies. Our experiments reveal that the message in abstract comic form elicited significantly more donations than text form (medium to large effect size=0.59). Incorporating social proof in the abstract comic message did not show a significant effect. Our studies have design implications: non-profits and governmental agencies interested in alleviating public goods dilemmas that share a similar structure to our experiment (single-shot task, distant, non-exclusive reward) ought to consider including messages in the abstract comic form as part of their online fund-raising campaign.
"Giving a little 'ayyy, I feel ya' to someone's personal post"
Authors: Lottridge Danielle , Andalibi Nazanin , Kim Joy , Kaye Jofish
Published: November 2019

Social media platforms offer people a variety of ways to interact, ranging from public broadcast posts, to comments on posts, to private messages, to paralinguistic interactions such as "liking" posts. In 2015, the commenting function "replies" was temporarily removed from Tumblr, providing a unique opportunity to study the deprivation of a standard social media feature. We administered a survey to investigate Tumblr users' perceptions and use of replies. Respondents reported that they used replies to simultaneously support others' performance and their own. Respondents compared replies to other digital interaction channels such as paralinguistic interactions, the sharing feature "reblogs", and "direct messages" (DMs), citing social considerations and norms around each. We used Goffman's performance theory to draw insights on the perceived semi-public / semi-private space of replies, which enabled users to perform supportive actions that did not belong in their main blogging identity frontstage but that were not backstage either. We discuss the limitation of performance theory to describe a presentation to a limited but unknown audience, and we describe how replies enabled new frontstages such as the delicate ramp up to the performance of intimacy in DMs. We discuss implications for performing support and identity on social media with audiences that are perceived as limited but are unknown.
Exploring Indicators of Digital Self-Harm with Eating Disorder Patients
Authors: Pater Jessica A. , Farrington Brooke , Brown Alycia , Reining Lauren E. , Toscos Tammy , Mynatt Elizabeth D.
Published: November 2019

Digital self-harm encompasses a variety of activities, including the use of social media to facilitate or amplify mental illness-related behaviors. To understand the extent of these behaviors and their impacts, we conducted an in-depth case study with three patients who are in recovery from an eating disorder. We collected survey data, conducted interviews reflecting back to their technology use during their active disease state, and reviewed up to 18 months of their social media data leading up to the start of their initial point of recovery. Through the triangulation of this data, we explore the role of social media and social technologies in relation to their eating disorder. By utilizing this methodology, we were able to provide a contextually rich and nuanced lens for exploring the impacts of digital self-harm on this group of patients. We found that patients acknowledged that the eating disordered content on social media had a negative impact on their health, often contributing to a worsening of the physical manifestations of their disorder. Conversely, while they actively consumed this content, our participants did not produce online content related to eating disordered activities or behaviors. Finally, we discuss the patterns within their social media data and how platform designers and operators could use these findings in the future through design considerations for future platform-based interventions.
Capturing Movement Decomposition to Support Learning and Teaching in Contemporary Dance
Authors: Rivière Jean-Philippe , Alaoui Sarah Fdili , Caramiaux Baptiste , Mackay Wendy E.
Published: November 2019

Our goal is to understand how dancers learn complex dance phrases. We ran three workshops where dancers learned dance fragments from videos. In workshop 1, we analyzed how dancers structure their learning strategies by decomposing movements. In workshop 2, we introduced MoveOn, a technology probe that lets dancers decompose video into short, repeatable clips to support their learning. This served as an effective analysis tool for identifying the changes in focus and understanding their decomposition and recomposition processes. In workshop 3, we compared the teacher's and dancers' decomposition strategies, and how dancers learn on their own compared to teacher-created decompositions. We found that they all ungroup and regroup dance fragments, but with different foci of attention, which suggests that teacher-imposed decomposition is more effective for introductory dance students, whereas personal decomposition is more suitable for expert dancers. We discuss the implications for designing technology to support analysis, learning and teaching of dance through movement decomposition.
"Point-of-Care Manufacturing"
Authors: Lakshmi Udaya , Hofmann Megan , Valencia Stephanie , Wilcox Lauren , Mankoff Jennifer , Arriaga Rosa I.
Published: November 2019

Maker culture is on the rise in healthcare with the adoption of consumer-grade fabrication technologies. However, little is known about the activities and resources involved in prototyping medical devices to improve patient care. In this paper, we refer to such activity asmedical making to report findings based on a qualitative study of stakeholder engagement in physical prototyping (making) experiences. We examine perspectives from diverse stakeholders including clinicians, engineers, administrators, and medical researchers. Through 18 semi-structured interviews with medical-makers in the US and Canada, we analyze making activity in medical settings. We find that medical makers share strategies to address risks, adopt labor roles, and acquire resources within traditional medical practice. Our findings outline how medical-makers mitigate risks for patient safety, collaborate with local and global stakeholder networks, and overcome constraints of co-location and material practices. We recommend a clinician-aided software system, partially-open repositories, and a collaborative skill-sharing social network to extend their strategies in support of medical making.
Reclaiming Stigmatized Narratives
Authors: Gallagher Ryan J. , Stowell Elizabeth , Parker Andrea G. , Foucault Welles Brooke
Published: November 2019

The social stigma looming over disclosures of sexual violence discourages many women from publicly sharing their stories, limiting their ability to seek support and obscuring the epidemic of sexual violence against women. By inviting women to share their ordinarily silenced stories, the hashtag #MeToo surfaced a network of survivors to confront this stigma. Through a mixed-methods analysis of over 1.8 million tweets posted during the first two weeks after #MeToo gained widespread popularity in 2017, we map the landscape of disclosures that emerged and disentangle the effects of network-level reciprocal disclosures, or disclosures made in reaction to seeing others disclose. We detail how survivors disclosed a diversity of sexual violence experiences in solidarity with others, composing nearly half of all authored tweets and comprising a disproportionate number of interactions within the #MeToo network. Further, we show that the more disclosures an individual potentially saw prior to disclosing, the more likely they were to share details with their disclosure. We argue that such network-level reciprocal disclosures may have reduced stigma, creating a counterpublic space safe for disclosure which, subsequently, generated more disclosures. Our work illustrates how feminist hashtag activism, like #MeToo, can unify individual and collective narratives to dismantle the stigma surrounding disclosures of sexual violence. Content warning: This article heavily discusses issues of sexual violence against women.
Cash, Digital Payments and Accessibility
Authors: Kameswaran Vaishnav , Hulikal Muralidhar Srihari
Published: November 2019

Despite the growing interest in digitization and money in HCI and CSCW, the use of cash and digital payments by people with disabilities has received scant attention. We present findings from a qualitative study of people with visual impairments' use of cash and digital payments in metropolitan India. Using ride-hailing services as an exemplar, we find that both cash and digital payments were inaccessible to participants. We use Perry and Ferreira's "moneywork" as a theoretical framework to highlight the "added" work necessitated by this inaccessibility; that is, the work done in addition to the interactional work necessary to complete financial transactions. We argue that this "added" work is instrumental in "making" payments accessible. We discuss how ride-hailing platforms mediated collaborations between drivers and riders in relation to payments, while still making "moneywork" essential. We provide recommendations to improve the accessibility of digital payments to facilitate greater economic inclusion.
'Is the Time Right Now?'
Authors: Norris Wendy , Voida Amy , Palen Leysia , Voida Stephen
Published: November 2019

Temporal coordination endures as a central topic in computer-supported cooperative work (CSCW) because information systems still struggle to adequately support varying representations of time in the context of collaborations that areboth temporally and geographically dispersed. Moreover, the adaptive practices of these broadly dispersed groups are still not well understood. We ask:How do globally distributed teams temporally coordinate to accomplish their work? We examine an extreme case of online temporal coordination: high-tempo information curation about the urgent humanitarian crisis following the 2017 Hurricane Maria landfall in Puerto Rico. Our analysis of synchronous chat transcripts and data artifacts produced by The Standby Task Force reveals how this digital humanitarian group establishes temporal coordination through different shared understandings of time relative to the crisis, the globally distributed work, and the collaborative information technologies. We make four contributions from our analysis: First, we developed a pluritemporal analytical framework that describes different forms of socially constructed time and disambiguates their meaning in talk. Next, we present empirical evidence of how this distributed team establishes shared temporal orders to collectively orient their work in time. Then, we describe how they reconcile multiple and conflicting instances of sociotemporal "disorder'' to enable productive work. Last, we reflect on the design implications for collaborative information systems informed by this work.
All Talk
Authors: Narayan Sneha , TeBlunthuis Nathan , Hale Wm Salt , Hill Benjamin Mako , Shaw Aaron
Published: November 2019

Prior research suggests that facilitating easier communication in social computing systems will increase both interpersonal interactions as well as group productivity. This study tests these claims by examining the impact of a new communication feature called "message walls" that allows for faster and more intuitive interpersonal communication in wikis. Using panel data from a sample of 275 wiki communities that migrated to message walls and a method inspired by regression discontinuity designs, we analyze these transitions and estimate the impact of the system's introduction. Although the adoption of message walls was associated with increased communication among all editors and newcomers, it had little effect on productivity, and was further associated with a decrease in article contributions from new editors. Our results imply that design changes that make communication easier in a social computing system may not translate to increased participation along other dimensions.
A Slow Algorithm Improves Users' Assessments of the Algorithm's Accuracy
Authors: Park Joon Sung , Barber Rick , Kirlik Alex , Karahalios Karrie
Published: November 2019

With computational algorithms making an increasing number of deeply consequential, and often problematic judgments on our behalf, there is a growing interest in slowing down technology to encourage users to reflect on judgments made by algorithms. Prior work in slow technology has established slowness as an agent of reflection and serendipity; however, it has been unclear whether this waiting time actually helps users gain useful insight or any other benefits as they make judgments using an algorithm. To this end, we conducted a series of online and in-person between-subject user studies in which we isolate the impact of an algorithm's speed on how users incorporate the algorithm's advice when making judgments in the context of simple visual recognition tasks. We find that our participants followed good quality algorithms more and bad quality algorithms somewhat less if the response time of the algorithm is slower. Furthermore, qualitative analysis of the in-person study interviews reveals that the waiting was not time wasted, but was often used to reflect on the task and the estimation process of themselves and the algorithm, and to compare and reevaluate the two processes. Based on these findings, we outline design implications of future algorithmic systems.
Complex, Contemporary, and Unconventional
Authors: Vigil-Hayes Morgan , Parkhurst Nicholet Deschine , Duarte Marisa
Published: November 2019

In the 2018 U.S. midterm elections, a record number of Native American candidates ran for office at all levels of government. To better understand how these 104 candidates intersected with Indigenous political issues and movements to increase Native American voter turnout, we study 723,269 tweets about or by these candidates and 15,476 tweets associated with the #NativeVote movement between October 6, 2018 and February 5, 2019. We use a mixed methods approach to identify issues that emerge in the Native Candidates data set, including issues of representation and protean usage of the "Make America Great Again" hashtag #maga. When examining the feeds of selected candidates, we find that there can be a disconnect between the issues that candidates align themselves with on social media and the issues that they are associated with by others. We also find evidence of Indigenous issues spanning a vast political spectrum and being coupled with other issues in different ways by different candidates and audiences. Finally, we examine the intersection between Native American candidates and the\#NativeVote movement to discover emergent issue networks, including networks around voter suppression and Indigenous political action. Critically, we discuss how our interdisciplinary Indigenous feminist approach to social media analysis illuminates issues of marginalized communities in both a systematic and inductive manner that allows us to discover new patterns and issues with limited a priori knowledge about a complex system.
"Hello AI": Uncovering the Onboarding Needs of Medical Practitioners for Human-AI Collaborative Decision-Making
Authors: Cai Carrie J. , Winter Samantha , Steiner David , Wilcox Lauren , Terry Michael
Published: November 2019

Although rapid advances in machine learning have made it increasingly applicable to expert decision-making, the delivery of accurate algorithmic predictions alone is insufficient for effective human-AI collaboration. In this work, we investigate the key types of information medical experts desire when they are first introduced to a diagnostic AI assistant. In a qualitative lab study, we interviewed 21 pathologists before, during, and after being presented deep neural network (DNN) predictions for prostate cancer diagnosis, to learn the types of information that they desired about the AI assistant. Our findings reveal that, far beyond understanding the local, case-specific reasoning behind any model decision, clinicians desired upfront information about basic, global properties of the model, such as its known strengths and limitations, its subjective point-of-view, and its overall design objective--what it's designed to be optimized for. Participants compared these information needs to the collaborative mental models they develop of their medical colleagues when seeking a second opinion: the medical perspectives and standards that those colleagues embody, and the compatibility of those perspectives with their own diagnostic patterns. These findings broaden and enrich discussions surrounding AI transparency for collaborative decision-making, providing a richer understanding of what experts find important in their introduction to AI assistants before integrating them into routine practice.
MP Remix
Authors: Salimian Hossein , Brooks Stephen , Reilly Derek
Published: November 2019

to create an integrated space. We consider an MR configuration in which collocated collaborators work around a tabletop display, while remote collaborators wear an HMD to interact with a connected virtual environment that gives a 3D perspective, and consider the impact of varying degrees of view congruence with their collaborators. In a within-subjects study with 18 groups of 3, groups completed task scenarios involving 3D object manipulation around a physical-virtual mapped tabletop. We compare a synchronized Tabletop display baseline and two MR conditions with different levels of view congruence: Fishtank and Hover. Fishtank has a high degree of congruence as it shares a top-down perspective of the 3D objects with the tabletop collaborators. The Hover condition has less view congruence since 3D content hovers front of the remote collaborator above the table. The MR conditions yielded higher self-reported awareness and co-presence than the Tabletop condition for both collocated and remote participants. Remote collaborators significantly preferred the MR conditions for manipulating shared 3D models and communicating with their collaborators. Our findings illustrate strengths and weaknesses of both MR techniques but show that more participants preferred the less-congruent Hover condition overall. Reasons include that it facilitated interaction and viewing 3D objects.
Design for Collaborative Information-Seeking
Authors: Hong Sungsoo (Ray) , Suh Minhyang (Mia) , Kim Tae Soo , Smoke Irina , Sien Sangwha , Ng Janet , Zachry Mark , Kim Juho
Published: November 2019

Although Collaborative Information-Seeking (CIS) is becoming prevalent as people engage in shared decision-making, interface components adopted in the most commonly used information seeking tools (e.g., search, filter, select, and sort) are designed for individual use. To deepen our understanding of (1) how such single-user designs affect people's consensus building processes in CIS and (2) how to devise an alternative design to improve current practices, we conducted two 4-week diary studies and observed how groups seek out places together. Our studies focus on social event coordination as a case where CIS is necessary and important. In Study 1, we examined the major challenges people encounter when performing CIS using their preferred tools. These challenges include difficulties in capturing mutual preferences, high communication cost, and disparity of work depending on a group member's perceived role as an organizer or invitee. We discovered that improving a group's shared understanding of the target information they seek (e.g., places, products) could potentially address the challenges. In Study 2, we designed, deployed, and evaluated ComeTogether, a novel system that supports a group's social event coordination. ComeTogether adopts Collaborative Dynamic Queries (C-DQ), an interface designed to allow a group to share their preferences regarding potential destinations. Study 2 results indicate that using C-DQ increased users' awareness of other group members' preferences in performing CIS, making their coordination more transparent, more inviting, and fairer than what their current practice allows. Meanwhile, ComeTogether improved communication efficiency of groups while presenting opportunities to learn about others and to discover new places. We provide implications for design that explain considerations for adopting C-DQ and identify future research directions.
Sorting Out Valuation in the Charity Shop
Authors: Elsden Chris , Symons Kate , Bunduchi Raluca , Speed Chris , Vines John
Published: November 2019

Recent work within HCI and CSCW has become attentive to the politics of data and metrics in order to highlight the implications of what counts and how. In this paper, we relate these discussions to the longstanding distinctions made between value and values. We introduce literature on 'Valuation Studies' and argue for understanding the politics of data through valuation - an ongoing social practice that transforms socially embedded values into different forms of more abstract value. This theoretical work is developed through an ethnographic study of contemporary UK charity shops, as a site focused on the labour of valuation, but embedded in both local and global values. Through this study, we consider implications for the intervention and design of 'data-driven innovation', with a particular focus on distributed ledger technologies. We argue that these technologies inevitably engage in valuation, and require careful attention to the ongoing processes by which value is translated and performed by different stakeholders.
From Nomadic Work to Nomadic Leisure Practice
Authors: Ferreira Pedro , Helms Karey , Brown Barry , Lampinen Airi
Published: November 2019

Mobility has long been a central concern in research within the Computer-Supported Cooperative Work (CSCW) community, particularly when it comes to work and how being on the move calls for reorganizing work practices. We expand this line of work with a focus on nomadic leisure practices. Based on interviews with eleven participants, we present a study that illuminates how digital technologies are used to shape and structure long-distance cycling. Our main analysis centers on bike touring as a nomadic leisure practice and on how it offers a radical departure from traditional modes of structuring work and life, and thus, complicates the relationship between work and leisure. We complement this with an account of managing the uncertainties of nomadicity by focusing on participants' experiences with arranging overnighting and network hospitality. We offer this study, firstly, as one response to the call for more diversity in the empirical cases drawn upon in theorizing nomadic work and leisure practices, but more productively, as an opportunity to reflect upon the temporal and spatial logics of digital technologies and platforms and how they frame our attitudes towards the interplay between work and leisure.
Maintainer Perspectives on Data-driven Transport Asset Management and the Future Role of the Internet-of-Things
Authors: Harding Mike , Rouncefield Mark , Davies Nigel
Published: November 2019

In this paper we present fieldwork findings from engagements with a cooperative group of strategic and operations transport maintainers, responsible for the maintenance of drainage infrastructure to mitigate the risk and impact of flooding on the network. Through transport maintainer perspectives from rail and highways sectors, we focus on developing an understanding of work-practices in the context of transport surface-water management, and how the recent acceleration towards 'data-driven' technologies in support of maintenance intervention decision-making (i.e. the work of coordinating the cleaning of drainage) is integrated and impacting on current work-practice. Furthermore, we document and consider how maintainers perceive the potential role of the Internet-of-Things (IoT) and highlight emerging opportunities and tensions that may arise ahead of its future design and implementation.
Provider Perspectives on Integrating Sensor-Captured Patient-Generated Data in Mental Health Care
Authors: Ng Ada , Kornfield Rachel , Schueller Stephen M. , Zalta Alyson K. , Brennan Michael , Reddy Madhu
Published: November 2019

The increasing ubiquity of health sensing technology holds promise to enable patients and health care providers to make more informed decisions based on continuously-captured data. The use of sensor-captured patient-generated data (sPGD) has been gaining greater prominence in the assessment of physical health, but we have little understanding of the role that sPGD can play in mental health. To better understand the use of sPGD in mental health, we interviewed care providers in an intensive treatment program (ITP) for veterans with post-traumatic stress disorder. In this program, patients were given Fitbits for their own voluntary use. Providers identified a number of potential benefits from patients' Fitbit use, such as patient empowerment and opportunities to reinforce therapeutic progress through collaborative data review and interpretation. However, despite the promise of sensor data as offering an "objective" view into patients' health behavior and symptoms, the relationships between sPGD and therapeutic progress are often ambiguous. Given substantial subjectivity involved in interpreting data from commercial wearables in the context of mental health treatment, providers emphasized potential risks to their patients and were uncertain how to adjust their practice to effectively guide collaborative use of the FitBit and its sPGD. We discuss the implications of these findings for designing systems to leverage sPGD in mental health care.?