Vision-Language Models (VLMs) are increasingly used by blind and low-vision (BLV) people to identify and understand products in their everyday lives, such as food, personal care items, and household goods. Despite their prevalence, we lack an empirical understanding of how common image quality issues—such as blur, misframing, and rotation—affect the accuracy of VLM-generated captions and whether the resulting captions meet BLV people’s information needs. Based on a survey of 86 BLV participants, we develop an annotated dataset of 1,859 product images from BLV people to systematically evaluate how image quality issues affect VLM-generated captions. While the best VLM achieves 98% accuracy on images with no quality issues, accuracy drops to 75% overall when quality issues are present, worsening considerably as issues compound. We discuss the need for model evaluations that center on disabled people’s experiences throughout the process and offer concrete recommendations for HCI and ML researchers to make VLMs more reliable for BLV people.

Due to large enrollments, undergraduate computer science (CS) courses often incorporate lectures that can scale to many students. However, there is strong evidence that students learn best through active meaning-making, particularly in collaboration with others. In this paper, we explore how students seek out opportunities to learn collaboratively during class time in a large introductory CS (CS1) course and how pedagogical decisions can create opportunities for such collaboration. We use an ethnographic approach to observe natural student interactions in a CS1 class, contributing to limited research exploring CS classroom activity through ethnographic observation. We find that students engage in frequent siding (i.e., side-talk and other backchanneling during class) to address their in-the-moment learning needs for clarification, tutoring, and support with debugging, as well as to co-construct new understandings and connect with others. We also find that students can meet some of these needs by siding with digital tools. From this, we introduce the concept of digital siding, in which a student turns to the Internet or AI to achieve a goal rather than a peer, and discuss benefits and drawbacks of peer and digital siding. Our data shows that siding happens often and serves important learning needs, providing a way for students to actively engage in learning despite the large scale of CS1. Therefore, we argue that instructors should not view siding purely as a distraction and provide design recommendations to help instructors promote siding in ways that support learning.

Real-time collaboration tools (e.g., videoconferencing or project management) are central to modern work but often pose significant accessibility challenges for blind and low vision (BLV) people.While these tools can support both in-person and remote collaboration, barriers to usability and access can hinder full workforce participation.Prior research has explored accessibility issues with specific tools, but broader insights into how BLV people use and experience mainstream collaboration platforms remain limited.We conducted an online survey with 155 BLV users, evaluating the ease of using 30 widely used collaboration tools.Findings show that Zoom is rated as the easiest tool to use, however, project management and whiteboarding tools are rated relatively difficult to use.Over half of the respondents reported that accessibility barriers negatively impact their collaboration, job performance, and career growth.We discuss the compounding effects of inaccessible collaborative tools and offer design recommendations for more inclusive digital workspaces.

Although knowledge workers are increasingly able to adopt remote and hybrid working arrangements and work productively, many organizations continue to question the effectiveness of remote work and focus on its concerns and challenges. Previous CSCW research shows that remote workers have limited awareness of other workers, require more explicit coordination, and feel excluded from in-person colleagues. Research also shows that adopting work practices and technologies that are remote work-friendly can offset many of these challenges. Identifying which effective practices and challenges are most helpful or hurtful to remote workers-and how workplace attributes (e.g., team structure; communication frequency; tool use) affect them-could strengthen organizations' strategies and policies for remote work. Through a theoretically-informed survey of 1,526 U.S. knowledge workers, we find many factors prior research has argued as essential to remote work, such as knowing your teammates personally, to be the least important for remote workers, and show how workplace attributes influence those perceptions. We provide theoretical and practical implications for future research for organizations that wish to support remote and hybrid work modalities.

The effects of social media platform usage on users' well-being have been a topic of significant discussion. Some evidence suggests that users sharing about themselves in ways that are perceived by themselves and others as ''authentic'' may benefit their well-being. BeReal is a social media platform that aims to encourage more authentic online behavior by constraining users' ability to selectively share content via a daily prompt to post whatever they are doing at that time. This rigid operationalization of authenticity, however, may be at odds with the rich and nuanced notions of authenticity observed in practice. Through an analysis of interviews with 25 BeReal users, we find that participants experienced two facets of authenticity that often did not align with BeReal's operationalization. Moreover, we find that participants' desire for authenticity was often in tension with their competing desires for privacy and autonomy, and their desire to reflect back on significant moments. We discuss how these tensions illustrate the challenges of designing for authenticity and add nuance to our understanding of authenticity on social media platforms.

Increasingly, crowdfunding is transforming financing for many people worldwide. Yet we know relatively little about how, why, and when funding outcomes are impacted by signaling between funders. We conduct two studies of \(N=500\) and \(N=750\) participants involved in crowdfunding to investigate the effect of “crowd signals,” i.e., certain characteristics deduced from the amounts and timing of contributions, on the decision to fund. In our first study, we find that, under a variety of conditions, contributions of heterogeneous amounts arriving at varying time intervals are significantly more likely to be selected than homogeneous contribution amounts and times. The impact of signaling is strongest among participants who are susceptible to social influence. The effect is remarkably general across different project types, fundraising goals, participant interest in the projects, and participants’ altruistic attitudes. Our second study using less strict controls indicates that the role of crowd signals in decision-making is typically unrecognized by participants. Our results underscore the fundamental nature of social signaling in crowdfunding. They highlight the importance of designing around these crowd signals and inform user strategies both on the project creator and funder side.

Exchange of peer-to-peer support in online Q&A communities plays an instrumental role in helping people learn and use complex software tools. While prior work has documented how disabled people support each other in finding accessible practices and workarounds in different contexts, research on understanding their participation in dedicated online Q&A communities has been limited. Through the analysis of 180 conversation threads consisting of 1140 posts in an online text-based Q&A community of blind and low-vision audio producers, we reveal various strategies members in this community use to formulate their queries and provide effective solutions regarding screen reader based navigation of complex graphical user interfaces. We reflect upon our findings to discuss the complexities blind and low-vision software users face in developing a shared understanding during collaborative troubleshooting through textual conversations and reimagine how online Q&A platforms could enhance peer-to-peer instructional support among screen reader users.

The maker movement has garnered significant attention as democratizing design; yet, recent work has called attention to the challenges disabled people encounter in making. Although researchers have built systems to improve accessibility of maker technologies, limited studies have centered disabled people’s engagement in traditional forms of making like fiber arts. We examine the practice of fabric pattern design among a community of blind weavers who create hand-woven products with sighted instructors. Grounded in seventeen interviews with blind weavers and sighted instructors, we built Simphony, an audio-tactile system that aims to support blind weavers in creating and perceiving patterns. Findings from eight design exploration sessions at the community studio reveal how blind weavers used Simphony to learn the process of pattern design and generate patterns with sighted instructors. We reflect on collaborative understanding of pattern design among blind and sighted individuals and discuss opportunities for integrating technological augmentations into traditional craftwork.

Ill-structured problems demand that people adopt sophisticated strategies for planning, seeking support, and using available resources along their work process. These practices involve a challenging monitoring and strategizing process that existing tools cannot support since they largely lack an understanding of an organization’s processes, social structures, venues, and tools. We introduce workplace programming for situationally-aware systems–an approach for encoding work situations using computational abstractions of an organization’s ways of working and surfacing support strategies at appropriate times and settings. With this approach, we implement Orchestration Scripts, a system that supports various situated work activities in a socio-technical organization. Through a case study and field study, we show how our approach encodes different aspects of working effectively and helps people identify situations to enact effective strategies using the available support opportunities. Our results show how a programmable technology can provide situated support in today’s workplaces.

Data science and machine learning provide indispensable techniques for understanding phenomena at scale, but the discretionary choices made when doing this work are often not recognized. Drawing from qualitative research practices, we describe how the concepts of positionality and reflexivity can be adapted to provide a framework for understanding, discussing, and disclosing the discretionary choices and subjectivity inherent to data science work. We first introduce the concepts of model positionality and computational reflexivity that can help data scientists to reflect on and communicate the social and cultural context of a model’s development and use, the data annotators and their annotations, and the data scientists themselves. We then describe the unique challenges of adapting these concepts for data science work and offer annotator fingerprinting and position mining as promising solutions. Finally, we demonstrate these techniques in a case study of the development of classifiers for toxic commenting in online communities.

Collaborative writing is an integral part of academic and professional work. Although some prior research has focused on accessibility in collaborative writing, we know little about how visually impaired writers work in real-time with sighted collaborators or how online editing tools could better support their work. Grounded in formative interviews and observations with eight screen reader users, we built Co11ab, a Google Docs extension that provides configurable audio cues to facilitate understanding who is editing (or edited) what and where in a shared document. Results from a design exploration with fifteen screen reader users, including three naturalistic sessions of use with sighted colleagues, reveal how screen reader users understand various auditory representations and use them to coordinate real-time collaborative writing. We revisit what collaboration awareness means for screen reader users and discuss design considerations for future systems.

Context-aware applications have the potential to act opportunistically to facilitate human experiences and activities, from reminding us of places to perform personal activities, to identifying coincidental moments to engage in digitally-mediated shared experiences. However, despite the availability of context-detectors and programming frameworks for defining how such applications should trigger, designers lack support for expressing their human concepts of a situation and the experiences and activities they afford (e.g., situations to toss a frisbee) when context-features are made available at the level of locations (e.g., parks). This paper introduces Affinder, a block-based programming environment that supports constructing concept expressions that effectively translate their conceptions of a situation into a machine representation using available context features. During pilot testing, we discovered three bridging challenges that arise when expressing situations that cannot be encoded directly by a single context-feature. To overcome these bridging challenges, Affinder provides designers (1) an unlimited vocabulary search for discovering features they may have forgotten; (2) prompts for reflecting and expanding their concepts of a situation and ideas for foraging for context-features; and (3) simulation and repair tools for identifying and resolving issues with the precision of concept expressions on real use-cases. In a comparison study, we found that Affinder’s core functions helped designers stretch their concepts of how to express a situation, find relevant context-features matching their concepts, and recognize when the concept expression operated differently than intended on real-world cases. These results show that Affinder and tools that support bridging can improve a designer’s ability to express their concepts of a human situation into detectable machine representations—thus pushing the boundaries of how computing systems support our activities in the world.

Work and learning communities have become increasingly networked to support their members in developing the skills to solve complex, real-world problems. Though disciplinary knowledge remains important to tackle these problems, working effectively in these modern-day communities of practice demands the ability for one to learn how to access networked support (e.g., venues, tools, resource guides, or peers) throughout the community for one's needs. Against this backdrop, we study networked orchestration--how community members access and learn to access networked supports--in a community of practice for undergraduate research training. Through field observations and in-depth interviews, we find that students in the networked research community dynamically engage with their mentors and peers across multiple venues throughout the week in order to identify, clarify, and resolve their needs. Mentors in the community monitor how students are engaging with the supports available in the network, and provide coaching on effective strategies when students are ineffective on their own. Finally, we surface the challenges involved in each of these processes and offer practical insights for future ecosystem-level networked orchestration technologies that have an understanding of the interactions occurring across the venues and tools in a community, and can support the learning and practice of effective access strategies. Our paper presents important insights for supporting people's work and learning needs in networked future workplaces and learning communities, and provides guidance on designing new technologies for supporting networked ways of working and learning.

Collaborative writing tools have been used widely in professional and academic organizations for many years. Yet, there has not been much work to improve screen reader access in mainstream collaborative writing tools. This severely affects the way people with vision impairments collaborate in ability-diverse teams. As a step toward addressing this issue, the present article aims at improving screen reader representation of collaborative features such as comments and track changes (i.e., suggested edits). Building on our formative interviews with 20 academics and professionals with vision impairments, we developed auditory representations that indicate comments and edits using non-speech audio (e.g., earcons, tone overlay), multiple text-to-speech voices, and contextual presentation techniques. We then performed a systematic evaluation study with 48 screen reader users that indicated that non-speech audio, changing voices, and contextual presentation can potentially improve writers’ collaboration awareness. We discuss implications of these results for the design of accessible collaborative systems.

Despite many available social technologies for connecting at a distance, we don't always find opportunities to actively engage in shared experiences and activities with friends and loved ones, even though this kind of interaction is associated with increased social closeness. To better support active engagement in shared experiences and activities while also making it convenient to find opportunities for interacting in this way, our work explores the design of Opportunistic Collective Experiences (OCEs), or social experiences powered by computer programs that identify opportune moments when users share situations across distance and structure shared activities in those situations. To support interacting with, programming, and executing OCEs, we developed Cerebro, a computational platform that consists of a mobile app that supports users? social interaction, an API for expressing the situations and activities that make up the interactional opportunity, and an opportunistic execution engine that checks for interactional opportunities and executes them when possible. Through a 20 day deployment study tested with groups of geographically-distributed college alumni (N=21), we found that OCEs promoted opportunities for active engagement; facilitated interactions that were socially connecting by structuring ways to engage in shared experiences and activities; and made actively engaging easier by identifying situations appropriate for interacting and structuring how to engage in activities in these situations. We contribute to CSCW (1) a novel interaction that facilitates engaging in shared experiences and activities at distance during coincidental moments; and (2) the design of systems to interact with, program, and execute these kinds of interactions.

Social networking sites are becoming increasingly popular venues for seeking information. To the extent that users can understand who knows what in their networks and target those friends appropriately, they can make effective use of the site as a knowledge base of information. This paper explores how targeting one's Facebook network when asking questions influences the breadth and quality of answers they receive. An experiment (N = 64) was conducted in which participants posted questions to their Facebook networks in four broadcast level conditions: status update to their full networks, status update to a custom subset of their networks, posting on a friend's Timeline, and sending a direct message. Results indicate that posting a question more broadly results in more information, which is moderated by perceptions of Facebook as a transactive memory system and as a source of social capital. However, informational and social value of responses is greatest when posting to a custom subset of their network. These results suggest that while targeting specific individuals may be the most effective means of gathering information in offline networks, the broadcast affordance of Facebook may be a more useful way to gather information on the site.?

Millions of people worldwide contribute content to peer production repositories that serve human information needs and provide vital world knowledge to prominent artificial intelligence systems. Yet, extreme gender participation disparities exist in which men significantly outnumber women. A central concern has been that due to self-focus bias, these disparities can lead to corresponding gender content disparities, in which content of interest to men is better represented than content of interest to women. This paper investigates the relationship between participation and content disparities in OpenStreetMap. We replicate findings that women are dramatically under-represented as OSM contributors, and observe that men and women contribute different types of content and do so about different places. However, the character of these differences confound simple narratives about self-focus bias: we find that on a proportional basis, men produced a higher proportion of contributions in feminized spaces compared to women, while women produced a higher proportion of contributions in masculinized spaces compared to men.

Advances in eye tracking technology have enabled new interaction techniques and gaze-based applications. However, the techniques for visualizing gaze information have remained relatively unchanged. We developed Iris, a tool to support the design of contextually relevant gaze visualizations. Iris allows users to explore displaying different features of gaze behavior including the current fixation point, duration, and saccades. Stylistic elements such as color, opacity, and smoothness can also be adjusted to give users creative and detailed control over the design of their gaze visualization. We present the Iris system and perform a user study to examine how participants can make use of the tool to devise contextually relevant gaze visualizations for a variety of collaborative tasks. We show that changes in color and opacity as well as variation in gaze trails can be adjusted to create meaningful gaze visualizations that fit the context of use.

Recent studies have identified various forms of bias in language-based models, raising concerns about the risk of propagating social biases against certain groups based on sociodemographic factors (e.g., gender, race, geography). In this study, we analyze the treatment of age-related terms across 15 sentiment analysis models and 10 widely-used GloVe word embeddings and attempt to alleviate bias through a method of processing model training data. Our results show significant age bias is encoded in the outputs of many sentiment analysis algorithms and word embeddings, and we can alleviate this bias by manipulating training data.

Collaborative writing tools have become ubiquitous in today's world and are used widely in many professional organizations and academic settings. Yet, we know little about how ability-diverse teams, such as those involving people with and without vision impairments, make use of collaborative writing tools. We report on interviews with 20 academics and professionals who are blind or visually impaired and perform collaborative writing with sighted colleagues. Our findings reveal that people with vision impairments perform collaborative writing activities through four interconnected processes, which include learning an ecosystem of (in)accessible tools, adapting to complexities of collaborative features, balancing the cost and benefit of accessibility, and navigating power dynamics within organizations. We discuss how our analysis contributes to theories of accessibility in collaboration and offers practical insights for future collaborative system design.

Participatory sensing systems in which people actively participate in the data collection process must account for both the needs of data contributors and the data collection goals. Existing approaches tend to emphasize one or the other, with opportunistic and directed approaches making opposing tradeoffs between providing convenient opportunities for contributors and collecting high-fidelity data. This paper explores a new, hybrid approach, in which collected data-even if low-fidelity initially-can provide useful information to data contributors and inspire further contributions. We realize this approach with 4X, a multi-stage data collection framework that first collects data opportunistically by requesting contributions at specific locations along users' routes and then uses collected data to direct users to locations of interest to make additional contributions that build data fidelity and coverage. To study the efficacy of 4X, we implemented 4X into LES, an application for collecting information about campus locations and events. Results from two field deployments (N = 95, N = 18) show that the 4X framework created 34% more opportunities for contributing data without increasing disruption, and yielded 49% more data by directing users to locations of interest. Our results demonstrate the value and potential of multi-stage, dynamic data collection processes that draw on multiple sources of motivation for data, and how they can be used to better meet data collection goals as data becomes available while avoiding unnecessary disruption.

It is our great pleasure to welcome you to this issue of the Proceedings of the ACM on Human- Computer Interaction, on the contributions of the research community Computer-Supported Cooperative Work and Social Computing (CSCW). This issue contains a carefully selected set of papers, accepted through our review process from among the 658 world-wide articles submitted by the Spring 2019 deadline. After the first round of peer review, 325 (49.4%) papers were invited to the Revise and Resubmit phase. After receiving the revised submissions, the external reviewers and the program committee reviewed all second round contributions. Finally, the program committee came together for a three-day online editorial committee meeting, held to allow for collective deliberation. Ultimately, 205 papers (31.2%) were accepted.

Online resources can help novice developers learn basic programming skills, but few resources support progressing from writing working code to learning professional web development practices. We address this gap by advancing Readily Available Learning Experiences, a conceptual approach for transforming all professional web applications into opportunities for authentic learning. This article presents Isopleth, a web-based platform that helps learners make sense of complex code constructs and hidden asynchronous relationships in professional web code. Isopleth embeds sensemaking scaffolds informed by the learning sciences to (1) expose hidden functional and event-driven relationships, (2) surface functionally related slices of code, and (3) support learners manipulating the provided code representations. To expose event-driven relationships, Isopleth implements a novel technique called Serialized Deanonymization to determine and visualize asynchronous functional relationships. To evaluate Isopleth, we conducted a case study across 12 professional websites and a user study with 14 junior and senior developers. Results show that Isopleth’s sensemaking scaffolds helped to surface implementation approaches in event binding, web application design, and complex interactive features across a range of complex professional web applications. Moreover, Isopleth helped junior developers improve the accuracy of their conceptual models of how features are implemented by 31% on average.

In remote collaboration, gaze visualizations are designed to display where collaborators are looking in a shared visual space. This type of gaze-based intervention can improve coordination, however researchers have yet to fully explore different gaze visualization techniques and develop a deeper understanding of the ways in which features of visualizations may interact with task attributes to influence collaborative performance. There are many ways to visualize characteristics of eye movements, such as a path connecting fixation points or a heat map illustrating fixation duration and coverage. In this study, we designed and evaluated three unique gaze visualizations in a remote search task. Our results suggest that the design of gaze visualizations affects performance, coordination, searching behavior, and perceived utility. Additionally, the degree of task coupling further influences the effect of gaze visualizations on performance and coordination. We then reflect on the value of gaze visualizations for remote work and discuss implications for the design of gaze-based interventions.

Computational approaches to text analysis are useful in understanding aspects of online interaction, such as opinions and subjectivity in text. Yet, recent studies have identified various forms of bias in language-based models, raising concerns about the risk of propagating social biases against certain groups based on sociodemographic factors (e.g., gender, race, geography). In this study, we contribute a systematic examination of the application of language models to study discourse on aging. We analyze the treatment of age-related terms across 15 sentiment analysis models and 10 widely-used GloVe word embeddings and attempt to alleviate bias through a method of processing model training data. Our results demonstrate that significant age bias is encoded in the outputs of many sentiment analysis algorithms and word embeddings. We discuss the models' characteristics in relation to output bias and how these models might be best incorporated into research.

Writing introductory help requests is a key part of develop-ing new professional connections, such as through email and other online messaging systems. This paper presents the design and an experimental evaluation of IntroAssist-a web-based tool that leverages cognitive apprenticeship in-structional methods to support writing introductory help requests through an expert-informed checklist, tagged peer examples, self-tagging, and suggested word limit. In a study of IntroAssist with novice entrepreneurs, we find that 1) expert raters consider help requests written with the tool as more effective, 2) participants are able to perform introduc-tory help seeking skills after the tool is removed, and 3) participants report being more likely to send help requests written with the tool. We present implications for the de-velopment of systems that support the initiation of profes-sional relationships.

We consider the challenge of motivating and coordinating large numbers of people to contribute to solving local, communal problems through their existing routines. In order to design such "on-the-go crowdsourcing" systems, there is a need for mechanisms that can effectively coordinate contributions to address problem solving needs in the physical world while leveraging people's existing mobility with minimal disruption. We thus introduce Hit-or-Wait, a general decision-theoretic mechanism that intelligently controls decisions over when to notify a person of a task, in ways that reason both about system needs across tasks and about a helper's changing patterns of mobility. Through simulations and a field study in the context of community-based lost-and-found, we demonstrate that using Hit-or-Wait enables a system to make efficient use of people's contributions with minimal disruptions to their routines without the need for explicit coordination. Interviews with field study participants further suggest that highlighting an individual's contribution to the global goal may help people value their contributions more.

As algorithmically-driven content curation has become an increasingly common feature of social media platforms, user resistance to algorithmic change has become more frequent and visible. These incidents of user backlash point to larger issues such as inaccurate understandings of how algorithmic systems work as well as mismatches between designer and user intent. Using a content analysis of 102,827 tweets from #RIPTwitter, a recent hashtag-based backlash to rumors about introducing algorithmic curation to Twitter's timeline, this study addresses the nature of user resistance in the form of the complaints being expressed, folk theories of the algorithmic system espoused by users, and how these folk theories potentially frame user reactions. We find that resistance to algorithmic change largely revolves around expectation violation, with folk theories acting as frames for reactions such that more detailed folk theories are expressed through more specific reactions to algorithmic change.

Why do people start new online communities? Previous research has studied what helps communities to grow and what motivates contributors, but the reasons that people create new communities in the first place remain unclear. We present the results of a survey of over 300 founders of new communities on the online wiki hosting site Wikia.com. We analyze the motivations and goals of wiki creators, finding that founders have diverse reasons for starting wikis and diverse ways of defining their success. Many founders see their communities as occupying narrow topics, and neither seek nor expect a large group of contributors. We also find that founders with differing goals approach community building differently. We argue that community platform designers can create interfaces that support the diverse goals of founders more effectively.

Online feedback exchange (OFE) systems are an increasingly popular way to test concepts with millions of target users before going to market. Yet, we know little about how designers make sense of this abundant feedback. This empirical study investigates how expert and novice designers make sense of feedback in OFE systems. We observed that when feedback conflicted with frames originating from the participant's design knowledge, experts were more likely than novices to question the inconsistency, seeking critical information to expand their understanding of the design goals. Our results suggest that in order for OFE systems to be truly effective, they must be able to support nuances in sensemaking activities of novice and expert users.

People utilize eye gaze as an important cue for monitoring attention and coordinating awareness. This study investigates how remote pairs make use of a graphical representation of their partner's eye-gaze during a tightly-coupled collaborative task. Our results suggest that reproducing shared gaze in a remote collaboration setting makes pairs more accurate when referring to linguistically complex objects by facilitating the production of efficient forms of deictic references. We discuss how the availability of gaze influences coordination strategies and implications for the design of shared gaze in remote collaboration systems.

Speakers often come to use similar words during conversation; that is, they come to exhibit lexical similarity. The extent to which this occurs is associated with many positive social outcomes. However, existing measures of lexical similarity are either highly labor intensive or too coarse in their temporal resolution. This limits the ability of researchers to study lexical similarity as it unfolds over the course of a conversation. We present a fully automated metric for tracking lexical similarity over time, and demonstrate it on individual conversations, explore general trends in aggregate conversational dynamics, and examine differences in how similarity tracks over time in groups with differing social outcomes.

Nonverbal, paralinguistic cues such as punctuation and emoticons are believed to be one of the mechanisms through which interpersonal relationship development takes place in text-based interactions. We use a novel experimental apparatus to manipulate these cues in a live Instant Message conversation. Results show a positive causal relationship of conversation duration and cue use on perceived affinity, and the relationship is contingent upon whether or not partners are able to see each other's cues. Further analysis of the dialogue reveals that reciprocity may play a central role in supporting this effect. We then demonstrate how one's cue use is influenced by a partner's cue use, and show that cues are often used in greeting and sign-off rituals.

Are one's individual biases stronger when mediated communication is used? This paper examines the role of self-esteem-related biases and communication channel during romantic couple conflict. Romantic couples communicated about a conflict either face-to-face (FtF) or via instant messenger (IM). Results revealed that for people with lower levels of self-esteem, their negative biases were triggered when they communicated with their partners via IM; people with lower levels of self-esteem had more negative assessments of the conflict discussion and of the impact of the discussion on the relationship when communicating via IM than when communicating FtF. At a theoretical level, this work deepens our understanding of how individual difference variables like self-esteem impact how individuals process information and communicate via technology. At a practical level, findings suggest that the use of mediated communication during conflict is more harmful to certain individuals than to others.

Recent years have seen the growth of physical crowdsourcing systems (e.g., Uber; TaskRabbit) that motivate large numbers of people to provide new and improved physical tasking and delivery services on-demand. In these systems, opportunistically relying on people to make convenient contributions may lead to incomplete solutions, while directing people to do inconvenient tasks requires high incentives. To increase people's willingness to participate and reduce the need to incentivize participation, we study on-the-go crowdsourcing as an alternative approach that suggests tasks along people’s existing routes that are conveniently on their way. We explore as a first step in this paper the design of task notification policies that decide when, where, and to whom to suggest tasks. Situating our work in the context of practical problems such as package delivery and lost-and-found searches, we conducted controlled experiments that show how small changes in task notification policy can influence individual participation and actions in significant ways that in turn affect system outcomes. We discuss the implications of our findings on the design of future on-the-go crowdsourcing technologies and applications.

Social media platforms and mobile applications increasingly include geographic features and services. While previous research has looked into how people perceive, interpret, and act on information available about a person, the spatial self, an individual's display of mobility through space for identity performance, is underexplored, especially in encounters with strangers. Strangers themselves offer a unique potential for exploring relational contexts and how those may relate to interpreting and reacting to the spatial self. We ran a 3 (map: personal, social, and task) x 3 (relationship: date, friend, coworker) x 2 (gender of participant: female, male) laboratory experiment with a mixed model design to see if and how the spatial self affects interest in future interaction. We find that maps, relationship, and gender all affect the ways in which people interpret and act on expressing interest in an individual. We discuss theoretical and design implications of how spatial selves affect this process.

This paper introduces the idea of presenting physical tasks into people’s existing routine so that people can contribute small tasks on-the-go with minimal effort. We present two on-the-go crowdsourcing systems: Libero for package delivery, and CrowdFound for finding lost items. To encourage contributions, we introduce notification techniques that present task opportunities when potential helpers are likely to accept. To direct people to regions where help is most needed, we introduce techniques for tracking a person’s location within a task region and directing their attention based on task history. Evaluation studies demonstrate the feasibility of on-the-go crowdsourcing and investigate questions over the likelihood of task completion, the perceived cost of disruption, and the effectiveness of tracking and coordination.

Providing the initiator of a conversation with awareness information about their target's availability can improve interruption timing. Providing this information, however, can be particularly challenging with mobile devices, which are carried by users in a range contexts and have limited audible and visual display possibilities due to possible background noise and small screen size. Haptic or tactile displays present a potentially useful alternative, as interaction with mobile devices is often by touch. This paper reports on a dual-task comparison of awareness information usage on a mobile variable-friction tactile display vs. a visual display under conditions that varied in task type and task workload. Participants using the tactile display performed marginally better on the primary task, but were less accurate and slower on the awareness task. However, there is evidence that some of the awareness task differences dissipated over time. Self-report data also suggests that people's experience with the tactile display was generally positive and improved over time.

Crowdfunding provides a new way for creatives to share their work and acquire resources from their social network to influence what new ideas are realized. Yet, we understand very little about this growing phenomenon. Grounded in existing work on social network analysis, we interview 58 crowdfunding project creators to investigate how crowdfunders use their social network to reach their campaign goals. We identified three main challenges, which include understanding network capabilities, activating network connections, and expanding network reach. From our findings, we develop initial design implications for support tools to help crowdfunding project creators better understand and leverage their social network.

This work explores the role of communication technologies during romantic couple conflict, and the impact that self-esteem has on behavior, preferences for communication channels, and attitudes about mediated communication during conflict. Results revealed that lower levels of self-esteem and communicating via text messaging (vs. face-to-face) were associated with increased distancing and perceived partner distancing behaviors. Lower levels of self-esteem and using mediated communication were also associated with a greater likelihood of thinking that a conflict had a negative impact on the relationship. Yet, there was no evidence to suggest that individuals with lower levels of self-esteem exhibited more negative behaviors and perceptions in text-based communication than in FtF communication. In addition, lower levels of self-esteem were associated with increased use of and preferences for text-based mediated communication over FtF communication during conflict. Overall, this study suggests that both self-esteem and communication channel impact the nature of romantic couple conflict.

In status message question asking (SMQA), members of social networking sites make use of status messages to express information needs to friends and contacts. We present findings from a laboratory study that examined 82 participants' SMQA behaviors in the broader context of online information seeking. When given the option of using a search engine and/or a social network, participants leveraged SMQA for 20% of their information needs, most often posing a question to their network in addition to issuing a query. We show the important roles played by the specificity of the information need and the perceived audience of a given network on routing decisions. We then demonstrate that routing decisions have varied effects on participants' satisfaction, information value, and trust of outcomes. In addition to highlighting the complementary advantages and disadvantages of search and SMQA, our findings suggest that search engines can better address a meaningful portion of people's information needs by integrating SMQA capabilities into their systems.

This work explores the act of channel switching, or switching between forms of face-to-face (FtF) and mediated communication (e.g., text messaging, instant messaging) during romantic couple conflict. Interviews were conducted with 24 individuals currently involved in a non-cohabitating romantic dating relationship of 3 months or longer. Results revealed that many patterns of channel switching are used during conflict, including switches from mediated to FtF communication and from FtF to mediated communication. In addition, participants had a number of interpersonal motivations for initiating a channel switch, including avoiding conflict escalation, managing one's emotions, and attempting to reach a resolution. Theoretical and design implications are discussed.

When pairs work together on a physical task, seeing a common workspace facilitates communication and benefits performance. When mediating such activities, however, the choice of technology can transform the visual information in ways that impact critical coordination processes. In this article we examine two coordination processes that are impacted by visual information—situation awareness and conversational grounding—which are theoretically distinct but often confounded in empirical research. We present three empirical studies that demonstrate how shared visual information supports collaboration through these two distinct routes. We also address how particular features of visual information interact with features of the task to influence situation awareness and conversational grounding, and further demonstrate how these features affect conversation and coordination. Experiment 1 manipulates the immediacy of the visual information and shows that immediate visual feedback facilitates collaboration by impro...

Aphasia is an acquired language disorder resulting from trauma or injury to language areas of the brain. Despite extensive research on the impact of aphasia on traditional forms of communication, little is known about the impact of aphasia on computer-mediated communication (CMC). In this study we asked whether the well-documented language deficits associated with aphasia can be detected in online writing of people with aphasia. We analyzed 150 messages (14,754 words) posted to an online aphasia support forum, by six people with aphasia and by four controls. Significant linguistic differences between people with aphasia and controls were detected, suggesting five putative linguistic HCI markers for aphasia. These findings suggest that interdisciplinary research on communication disorders and CMC has both applied and theoretical implications.

We present Omnipedia, a system that allows Wikipedia readers to gain insight from up to 25 language editions of Wikipedia simultaneously. Omnipedia highlights the similarities and differences that exist among Wikipedia language editions, and makes salient information that is unique to each language as well as that which is shared more widely. We detail solutions to numerous front-end and algorithmic challenges inherent to providing users with a multilingual Wikipedia experience. These include visualizing content in a language-neutral way and aligning data in the face of diverse information organization strategies. We present a study of Omnipedia that characterizes how people interact with information using a multilingual lens. We found that users actively sought information exclusive to unfamiliar language editions and strategically compared how language editions defined concepts. Finally, we briefly discuss how Omnipedia generalizes to other domains facing language barriers.

Prior scholarship on Wikipedia's collaboration processes has examined the properties of either editors or articles, but not the interactions between both. We analyze the coauthorship network of Wikipedia articles about breaking news demanding intense coordination and compare the properties of these articles and the editors who contribute to them to articles about contemporary and historical events. Using p*/ERGM methods to test a multi-level, multi-theoretical model, we identify how editors' attributes and editing patterns interact with articles' attributes and authorship history. Editors' attributes like prior experience have a stronger influence on collaboration patterns, but article attributes also play significant roles. Finally, we discuss the implications our findings and methods have for understanding the socio-material duality of collective intelligence systems beyond Wikipedia.

Mobile and handheld devices have become platforms to support remote collaboration. But, their small form-factor may impact the effectiveness of the visual feedback channel often used to help users maintain an awareness of their partner's activities during synchronous collaborative tasks. We investigated how visual and tactile feedback affects collaboration on mobile devices, with emphasis on spatial coordination in a shared workspace. From two user studies, our results highlight different benefits of each feedback channel in collaborative handheld systems. Visual feedback can provide precise spatial information for collaborators, but degrades collaboration when the feedback is occluded, and sometimes can distract the user's attention. Spatial tactile feedback can reduce the overload of information in visual space and gently guides the user's attention to an area of interest. Our results also show that visual and tactile feedback can complement each other, and systems using both feedback channels can support better spatial coordination than systems using only one form of feedback.

Exploratory search, in which a user investigates complex concepts, is cumbersome with today's search engines. We present a new exploratory search approach that generates interactive visualizations of query concepts using thematic cartography (e.g. choropleth maps, heat maps). We show how the approach can be applied broadly across both geographic and non-geographic contexts through explicit spatialization, a novel method that leverages any figure or diagram -- from a periodic table, to a parliamentary seating chart, to a world map -- as a spatial search environment. We enable this capability by introducing explanatory semantic relatedness measures. These measures extend frequently-used semantic relatedness measures to not only estimate the degree of relatedness between two concepts, but also generate human-readable explanations for their estimates by mining Wikipedia's text, hyperlinks, and category structure. We implement our approach in a system called Atlasify, evaluate its key components, and present several use cases.

Nonparametric data from multi-factor experiments arise often in human-computer interaction (HCI). Examples may include error counts, Likert responses, and preference tallies. But because multiple factors are involved, common nonparametric tests (e.g., Friedman) are inadequate, as they are unable to examine interaction effects. While some statistical techniques exist to handle such data, these techniques are not widely available and are complex. To address these concerns, we present the Aligned Rank Transform (ART) for nonparametric factorial data analysis in HCI. The ART relies on a preprocessing step that "aligns" data before applying averaged ranks, after which point common ANOVA procedures can be used, making the ART accessible to anyone familiar with the F-test. Unlike most articles on the ART, which only address two factors, we generalize the ART to N factors. We also provide ARTool and ARTweb, desktop and Web-based programs for aligning and ranking data. Our re-examination of some published HCI results exhibits advantages of the ART.

To create intelligent collaborative systems able to anticipate and react appropriately to users' needs and actions, it is crucial to develop a detailed understanding of the process of collaborative reference. We developed a dyadic eye tracking methodology and metrics for studying the multimodal process of reference, and applied these techniques in an experiment using a naturalistic conversation elicitation task. We found systematic differences in linguistic and visual coordination between pairs of mobile and seated participants. Our results detail measurable interactions between referential form, gaze, and spatial context and can be used to enable the development of more natural collaborative user interfaces.

For large global enterprises, providing adequate resources for organizational acculturation, the process in which employees learn about an organization's culture, remains a challenge. We present results from a survey of 802 users from an enterprise social networking site that identifies two groups of employees (new to the company and geographically distant from headquarters) that perceive higher benefit from using a SNS to learn about the organization's values and beliefs. In addition, we observe regional differences in viewing behaviors between two groups of new employees. These results suggest that a SNS can also potentially contribute to the information-seeking and sense-making activities that underlie organization acculturation.

Despite the prevalent use of group brainstorming for problem solving and decision-making within organizations, brainstorming sessions often lack focus and fail to produce quality ideas. We describe Momentum, a tool that elicits topic-oriented responses prior to a group brainstorm. In an exploratory study, we found qualitative differences in task focus, quality and rate of ideation, and efficiency of storytelling between users and non-users of the tool.

This study explores language's fragmenting effect on user-generated content by examining the diversity of knowledge representations across 25 different Wikipedia language editions. This diversity is measured at two levels: the concepts that are included in each edition and the ways in which these concepts are described. We demonstrate that the diversity present is greater than has been presumed in the literature and has a significant influence on applications that use Wikipedia as a source of world knowledge. We close by explicating how knowledge diversity can be beneficially leveraged to create "culturally-aware applications" and "hyperlingual applications".

The "localness" of participation in repositories of user-generated content (UGC) with geospatial components has been cited as one of UGC's greatest benefits. However, the degree of localness in major UGC repositories such as Flickr and Wikipedia has never been examined. We show that over 50 percent of Flickr users contribute local information on average, and over 45 percent of Flickr photos are local to the photographer. Across four language editions of Wikipedia, however, we find that participation is less local. We introduce the spatial content production model (SCPM) as a possible factor in the localness of UGC, and discuss other theoretical and applied implications.

Although Wikipedia has increasingly attracted attention for its in-depth and timely coverage of breaking news stories, the social dynamics of how Wikipedia editors process breaking news items has not been systematically examined. Through a 3-month study of 161 deliberations over whether a news item should appear on Wikipedia's front page, we demonstrate that elite users fulfill a unique gatekeeping role that permits them to leverage their community position to block the promotion of inappropriate items. However, these elite users are unable to promote their supported news items more effectively than other types of editors. These findings suggest that "one-sided gatekeeping" may reflect a crucial stasis in social media where the community has to balance the experience of its elite users while encouraging contributions from non-elite users.

This study explores how the design of visual display configurations relates to linguistic expressions. Twenty-five participants performed a series of object identification and narrative Description tasks on either a large wall-sized or small desktop display. Results revealed that during the Description tasks, large display users produced significantly greater rates of local deictic references than small display users, but in the identification tasks, the rates were similar for both large and small display users. Implications for the design of interactive technologies are discussed.

This paper examines how different forms of linguistic similarity in a text-chat environment relate to the establishment of interpersonal trust. Sixty-two pairs played an iterative social dilemma investment game and periodically communicated via Instant Messenger (IM). Novel automated and manual analysis techniques identify linguistic similarity at content, structural and stylistic levels. Results reveal that certain types of content (some positive emotion words, task-related words), structural (verb tense, phrasal entrainment), and stylistic (emoticons) similarity characterize high trusting pairs while other types of similarity (e.g., negative emotion words) characterize low trusting pairs. Contrary to previous literature, this suggests that not all similarity is good similarity.

Being able to automatically perceive a variety of emotions from text alone has potentially important applications in CMC and HCI that range from identifying mood from online posts to enabling dynamically adaptive interfaces. However, such ability has not been proven in human raters or computational systems. Here we examine the ability of naive raters of emotion to detect one of eight emotional categories from 50 and 200 word samples of real blog text. Using expert raters as a 'gold standard', naive-expert rater agreement increased with longer texts, and was high for ratings of joy, disgust, anger and anticipation, but low for acceptance and 'neutral' texts. We discuss these findings in light of theories of CMC and potential applications in HCI.

Emotion is central to human interactions, and automatic detection could enhance our experience with technologies. We investigate the linguistic expression of fine-grained emotion in 50 and 200 word samples of real blog texts previously coded by expert and naive raters. Content analysis (LIWC) reveals angry authors use more affective language and negative affect words, and that joyful authors use more positive affect words. Additionally, a co-occurrence semantic space approach (LSA) was able to identify fear (which naive human emotion raters could not do). We relate our findings to human emotion perception and note potential computational applications.

This study examines the relationship between linguistic mimicry and trust establishment in a text-chat environment. Twenty-six participant pairs engaged in a social dilemma investment game and chatted via Instant Messenger (IM) after every five rounds of investment. Results revealed that, within chat sessions, lexical mimicry (repetition of words or word phrases by both partners) was significantly higher for high-trusting pairs than for low-trusting pairs, but that lexical mimicry across chat sessions was significantly higher for low-trusting pairs than for high-trusting pairs. Theoretical and applied implications are discussed.

A Situated Conversational Agent (SCA) is an agent that engages in dialog about the context within which it is embedded. An SCA is distinguished from non-situated conversational agents by an intimate connection of the agent's dialog to its embedding context, and by intricate dependencies between its linguistic and physical actions. Constructing an SCA that can interact naturally with users while engaged in collaborative physical tasks requires the agent to interleave decision making under uncertainty, action execution, and observation while maximizing expected utility over a sequence of interactions. These requirements can be fulfilled by modeling an SCA as a partially observable Markov decision process (POMDP). We show how POMDPs can be used to formalize and implement psycholinguistic proposals on how situated dialog participants collaborate in order to make and ground dialog contributions.

A number of recent studies have demonstrated that groups benefit considerably from access to shared visual information. This is due, in part, to the communicative efficiencies provided by the shared visual context. However, a large gap exists between our current theoretical understanding and our existing models. We address this gap by developing a computational model that integrates linguistic cues with visual cues in a way that effectively models reference during tightly-coupled, task-oriented interactions. The results demonstrate that an integrated model significantly outperforms existing language-only and visual-only models. The findings can be used to inform and augment the development of conversational agents, applications that dynamically track discourse and collaborative interactions, and dialogue managers for natural language interfaces.

Cyber foraging is the transient and opportunistic use of compute servers bymobile devices. The short market life of such devices makes rapid modification of applications for remote execution an important problem. We describe a solution that combines a "little language" for cyber foraging with an adaptive runtime system. We report results from a user study showing that even novice developers are able to successfully modify large, unfamiliar applications in just a few hours. We also show that the quality of novice-modified and expert-modified applications are comparable in most cases.

A problem with the location-free nature of cell phones is that callers have difficulty predicting receivers' states, leading to inappropriate calls. One promising solution involves helping callers decide when to interrupt by providing them contextual information about receivers. We tested the effectiveness of different kinds of contextual information by measuring the degree of agreement between receivers' desires and callers' decisions. In a simulation, five groups of participants played the role of ‘Callers’, choosing between making calls or leaving messages, and a sixth group played the role of ‘Receivers’, choosing between receiving calls or receiving messages. Callers were provided different contextual information about Receivers' locations, their cell phones' ringer state, the presence of others, or no information at all. Callers provided with contextual information made significantly more accurate decisions than those without it. Our results suggest that different contextual information generates different kinds of improvements: more appropriate interruptions or better avoidance of inappropriate interruptions. We discuss the results and implications for practice in the light of other important considerations, such as privacy and technological simplicity.

When pairs work together on a physical task, seeing a common workspace benefits their performance and transforms their use of language. Previous results have demonstrated that visual information helps collaborative pairs to understand the current state of their task, ground their conversations, and communicate efficiently. However, collaborative technologies often impinge on the visual information needed to support successful collaboration. One example of this is the introduction of delayed visual feedback in a collaborative environment. We present results from two studies that detail the form of the function that describes the relationship between visual delay and collaborative task performance. The first study precisely demonstrates how a range of visual delays differentially impact performance and the collaborative strategies employed. The second study describes how parameters of the task, such as the dynamics of the visual environment, reduce the amount of delay that can be tolerated.

Large wall-sized displays are becoming prevalent. Although researchers have articulated qualitative benefits of group work on large displays, little work has been done to quantify the benefits for individual users. In this article we present four experiments comparing the performance of users working on a large projected wall display to that of users working on a standard desktop monitor. In these experiments, we held the visual angle constant by adjusting the viewing distance to each of the displays. Results from the first two experiments suggest that physically large displays, even when viewed at identical visual angles as smaller ones, help users perform better on mental rotation tasks. We show through the experiments how these results may be attributed, at least in part, to large displays immersing users within the problem space and biasing them into using more efficient cognitive strategies. In the latter two experiments, we extend these results, showing the presence of these effects with more complex tasks, such as 3D navigation and mental map formation and memory. Results further show that the effects of physical display size are independent of other factors that may induce immersion, such as interactivity and mental aids within the virtual environments. We conclude with a general discussion of the findings and possibilities for future work.

How much history of the dialogue should a chat client include? Some chat clients have minimized the dialogue history to deploy the space for other purposes. A theory of conversational coordination suggests that stripping away history raises the cost of conversational grounding, creating problems for both writers and readers. To test this proposition and inform design, we conducted an experiment in which one person instructed another on how to solve a simple puzzle. Participants had chat clients that showed either a single conversational turn or six of them. Having the dialogue history helped collaborators communicate efficiently and led to faster and better task performance. The dialogue history was most useful when the puzzles were more linguistically complex and when instructors could not see the work area. We present evidence of participants adapting their discourse to partially compensate for deficits in the communication media.

Previous results have shown that users perform better on spatial orientation tasks involving static 2D scenes when working on physically large displays as compared to small ones. This was found to be true even when the displays presented the same images at equivalent visual angles. Further investigation has suggested that large displays may provide a greater sense of presence, which biases users into adopting more efficient strategies to perform tasks. In this work, we extend those findings, demonstrating that users are more effective at performing 3D virtual navigation tasks on large displays. We also show that even though interacting with the environment affects performance, effects induced by interactivity are independent of those induced by physical display size. Together, these findings allow us to derive guidelines for the design and presentation of interactive 3D environments on physically large displays.

A shared visual workspace allows multiple people to see similar views of objects and environments. Prior empirical literature demonstrates that visual information helps collaborators understand the current state of their task and enables them to communicate and ground their conversations efficiently. We present an empirical study that demonstrates how action replaces explicit verbal instruction in a shared visual workspace. Pairs performed a referential communication task with and without a shared visual space. A detailed sequential analysis of the communicative content reveals that pairs with a shared workspace were less likely to explicitly verify their actions with speech. Rather, they relied on visual information to provide the necessary communicative and coordinative cues.

Large wall-sized displays are becoming prevalent. Although researchers have articulated qualitative benefits of group work on large displays, little work has been done to quantify the benefits for individual users. We ran two studies comparing the performance of users working on a large projected wall display to that of users working on a standard desktop monitor. In these studies, we held the visual angle constant by adjusting the viewing distance to each of the displays. Results from the first study indicate that although there was no significant difference in performance on a reading comprehension task, users performed about 26% better on a spatial orientation task done on the large display. Results from the second study suggest that the large display affords a greater sense of presence, allowing users to treat the spatial task as an egocentric rather than an exocentric rotation. We discuss future work to extend our findings and formulate design principles for computer interfaces and physical workspaces.

When virtual teams need to establish trust at a distance, it is advantageous for them to use rich media to communicate. We studied the emergence of trust in a social dilemma game in four different communication situations: face-to-face, video, audio, and text chat. All three of the richer conditions were significant improvements over text chat. Video and audio conferencing groups were nearly as good as face-to-face, but both did show some evidence of what we term delayed trust (slower progress toward full cooperation) and fragile trust (vulnerability to opportunistic behavior)

A shared visual workspace is one where multiple people can see the same objects at roughly the same time. We present findings from an experiment investigating the effects of shared visual space on a collaborative puzzle task. We show that having the shared visual space helps collaborators understand the current state of their task and enables them to communicate and ground their conversations efficiently. These processes are associated with faster and better task performance. Delaying the visual update in the space reduces benefits and degrades performance. The shared visual space is more useful when tasks are visually complex or when actors have no simple vocabulary for describing their world. We find evidence for the ways in which participants adapt their discourse processes to their level of shared visual information.