This study addresses two currently open questions about how behaviors of online community members influence others’ responses to misinformation. First, in contrast to prior work, it directly measures norm perception to address whether (1) norm perception actually acts as a mediator, (2) others’ behaviors directly influence individuals’ responses to misinformation, (3) both direct and mediated effects occur. Second, it investigates norm perceptions about a behavior that is not readily observable in online communities, but is prone to misinformation, specifically, vaccination. To do so, it experimentally manipulates the prevalence of communicating about vaccination (an unobservable behavior) within an online community. The results demonstrate no evidence of a direct effect—the causal relationship between prevalence of communicating a behavior and intentions to respond to misinformation only occurs via norm perception as a mediator. The paper highlights implications of these findings for designing community-centered interventions to influence perceived norms, thereby mitigating misinformation spread and impacts.

How do privacy experts and lay persons differ? We investigate this question using data about the use of privacy-enhancing technologies and strategies from 128 surveys and 17 follow-up interviews with two populations: privacy experts (i.e., privacy researchers and professionals) and privacy laypersons. Findings reveal that both experts and laypersons use common privacy strategies, but experts employ a broader range of strategies, favor open source technologies, and possess a more technical understanding of internet privacy risks and technologies such as onion routing and tracking algorithms. We characterize these differences in terms of sociological habitus, where experts and laypersons differ not only in technical skill but also in broader conceptualizations and practices. From this characterization, we make recommendations for technology design practices, as well as legal and pedagogical implications, that can help decenter the experiences of privacy experts and accommodate privacy laypersons' preferences and habits.

This article considers how subjectivities are enlivened in algorithmic systems. We first review related literature to clarify how we see “subjectivities” as emerging through a tangled web of processes and actors. We then offer two case studies exemplifying the emergence of algorithmic subjectivities: one involving computational topic modeling of blogs written by parents with children on the autism spectrum and one involving algorithmic moderation of social media content. Drawing on these case studies, we then articulate a series of qualities that characterizes algorithmic subjectivities. We also compare and contrast these qualities with a number of related concepts from prior literature to articulate how algorithmic subjectivities constitute a novel theoretical contribution, as well as how it offers a focal lens for future empirical investigation and for design. In short, this article points out how certain worlds are being made and/or being made possible via algorithmic systems, and it asks Human–Computer Interaction (HCI) to consider what other worlds might be possible.

Social norms play a significant role in how conspiratorial content and related misinformation impact online communities. However, less is understood about the mechanisms by which particular aspects of a community may drive perceptions of social norms in the community. Using anti-vaccine conspiracies as a testbed, this paper experimentally examines three such features and their relationships : prevalence of conspiratorial content, community response, and explicit community rules. Results show that prevalence of content has a significant effect on norm perceptions, while the results did not support the effects of explicit rule on norm perceptions. However, these effects can be mitigated by the way a community responds to such content. Furthermore, perceived norms also influence other expectations about the community, from escalated behaviors to belief in other conspiracy theories. The paper concludes by highlighting the implications of these findings for online platform design, for community governance, and for future research about the relationships among conspiratorial content and norm perceptions.

The emergent, dynamic nature of privacy concerns in a shifting sociotechnical landscape creates a constant need for privacy-related resources and education. One response to this need is community-based privacy groups. We studied privacy groups that host meetings in diverse urban communities and interviewed the meeting organizers to see how they grapple with potentially varied and changeable privacy concerns. Our analysis identified three features of how privacy groups are organized to serve diverse constituencies: situating (finding the right venue for meetings), structuring (finding the right format/content for the meeting), and providing support (offering varied dimensions of assistance). We use these findings to inform a discussion of “privacy pluralism” as a perennial challenge for the HCI privacy research community, and we use the practices of privacy groups as an anchor for reflection on research practices.

Prior work has identified a variety of factors that drive the way people identify and respond to misinformation. Such factors include confirmation bias, perceived credibility of the information source, individual media literacy, social norms, and others. This paper reviews the interventions designed to address misinformation and examines how various underlying mechanisms of response to misinformation are operationalized and implemented in the reviewed interventions. Key findings show that most prior work to address misinformation heavily focuses on individual pieces of misinformation and the actions individuals take in response to those individual pieces. These individualistic approaches, we argue, overlook the other drivers of responses to misinformation, such as individuals' prior beliefs and the social contexts in which misinformation is encountered. Additionally, the analysis shows that an individualistic focus on misinformation draws attention away from the systemic nature and consequences of misinformation. This paper argues that to overcome the limitation of individualistic approaches to addressing misinformation, future interventions need to expand their scope beyond individualistic approaches. As one way to do so, it discusses leveraging the impacts of community factors that impact the spread and impacts of misinformation. The paper concludes by using social norms as an example to illustrate how a focus on community factors might work in practice.

As AI-mediated communication (AI-MC) becomes more prevalent in everyday interactions, it becomes increasingly important to develop a rigorous understanding of its effects on interpersonal relationships and on society at large. Controlled experimental studies offer a key means of developing such an understanding, but various complexities make it difficult for experimental AI-MC research to simultaneously achieve the criteria of experimental realism, experimental control, and scalability. After outlining these methodological challenges, this paper offers the concept of methodological middle spaces as a means to address these challenges. This concept suggests that the key to simultaneously achieving all three of these criteria is to abandon the perfect attainment of any single criterion. This concept's utility is demonstrated via its use to guide the design of a platform for conducting text-based AI-MC experiments. Through a series of three example studies, the paper illustrates how the concept of methodological middle spaces can inform the design of specific experimental methods. Doing so enabled these studies to examine research questions that would have been either difficult or impossible to investigate using existing approaches. The paper concludes by describing how future research could similarly apply the concept of methodological middle spaces to expand methodological possibilities for AI-MC research in ways that enable contributions not currently possible.

The rise of automated text processing systems has led to the development of tools designed for a wide variety of application domains. These technologies are often developed to support non-technical users such as domain experts and are often developed in isolation of the tools primary user. While such developments are exciting, less attention has been paid to domain experts’ expectations about the values embedded in these automated systems. As a step toward addressing that gap, we examined values expectations of journalists and legal experts. Both these domains involve extensive text processing and place high importance on values in professional practice. We engaged participants from two non-profit organizations in two separate co-speculation design workshops centered around several speculative automated text processing systems. This study makes three interrelated contributions. First, we provide a detailed investigation of domain experts’ values expectations around future NLP systems. Second, the speculative design fiction concepts, which we specifically crafted for these investigative journalists and legal experts, illuminated a series of tensions around the technical implementation details of automation. Third, our findings highlight the utility of design fiction in eliciting not-to-design implications, not only about automated NLP but also about technology more broadly. Overall, our study findings provide groundwork for the inclusion of domain experts values whose expertise lies outside of the field of computing into the design of automated NLP systems.

Two general approaches are common for evaluating automatically generated labels in topic modeling: direct human assessment; or performance metrics that can be calculated without, but still correlate with, human assessment. However, both approaches implicitly assume that the quality of a topic label is single-dimensional. In contrast, this paper provides evidence that human assessments about the quality of topic labels consist of multiple latent dimensions. This evidence comes from human assessments of four simple labeling techniques. For each label, study participants responded to several items asking them to assess each label according to a variety of different criteria. Exploratory factor analysis shows that these human assessments of labeling quality have a two-factor latent structure. Subsequent analysis demonstrates that this multi-item, two-factor assessment can reveal nuances that would be missed using either a single-item human assessment of perceived label quality or established performance metrics. The paper concludes by suggesting future directions for the development of human-centered approaches to evaluating NLP and ML systems more broadly.

Abstract Recent developments in critical information visualization have brought the field's attention to political, feminist, ethical, and rhetorical aspects of data visualization. However, less work has explored the interplay between design decisions and political ramifications—structures of authority, means of representation, etc. In this paper, we build upon these critical perspectives and highlight the political aspect of civic text visualization especially in the context of democratic decision‐making. Based on a critical analysis of survey papers about text visualization in general, followed by a review on the status quo of text visualization in civics, we argue that civic text visualization inherits an exclusively analytic framing. This framing leads to a series of issues and challenges in the fundamentally political context of civics, such as misinterpretation of data, missing minority voices, and excluding the public from decision making processes. To span this gap between political context and analytic framing, we provide a series of two‐pole conceptual dimensions, such as from singular user to multiple relationships, and from complexity to inclusivity of visualization design. For each dimension, we discuss how the tensions between these poles can help surface the political ramifications of design decisions in civic text visualization. These dimensions can thus help visualization researchers, designers, and practitioners attend more intentionally to these political aspects and inspire their design choices. We conclude by suggesting that these dimensions may be useful for visualization design across a variety of application domains, beyond civic text visualization.

For over a quarter century, GROUP has offered a premier yet intimate and welcoming venue for agenda-setting, diverse research. Although the traditional focus of the conference is on supporting group work, it has expanded to include research from computer-supported cooperative work, sociotechnical studies, practice-centered computing, human-computer interaction, computersupported collaborative learning, participatory technology design, and other related areas. The work presented in this issue embodies that interdisciplinary ethos. Papers in this issue cover a wide range topics, from human-AI collaboration, to collaboration in virtual reality, to perceptions of privacy and security, to the myriad impacts of the COVID-19 pandemic. The application domains are similarly wide ranging, from health data, to civic engagement, to educational settings, to government provision of social services. Similar to the 2021 issue, this issue also continues the tradition of design fiction at GROUP. This issue of PACM:HCI brings you papers from the planned 2022 ACMConference on Supporting Group Work (GROUP 2022). Typically, the GROUP conference occurs every two years. However, research developments do not necessarily follow conference deadline cycles. Thus, the GROUP conference offers authors the opportunity to submit to multiple waves. The first wave of papers for this conference were published in July 2021 in Volume 5 of PACM:HCI, and papers from this current issue were first submitted in May 2021. Both of these sets of papers published as part of the planned GROUP 2022 conference were authored and reviewed during the COVID-19 pandemic. These papers represent commendable volumes of hard work and resilience, not just from the authors, but also from the reviewers, the program committee, and the conference organizers. Additionally, the pandemic forced a major change to the conference at which these papers will be presented.

Eating disorders (EDs) constitute a mental illness with the highest mortality. Today, mobile health apps provide promising means to ED patients for managing their condition. Apps enable users to monitor their eating habits, thoughts, and feelings, and offer analytic insights for behavior change. However, not only have scholars critiqued the clinical validity of these apps, their underlying design principles are not well understood. Through a review of 34 ED apps, we uncovered 11 different data types ED apps collect, and 9 strategies they employ to support collection and reflection. Drawing upon personal health informatics and visualization frameworks, we found that most apps did not adhere to best practices on what and how data should be collected from and reflected to users, or how data-driven insights should be communicated. Our review offers suggestions for improving the design of ED apps such that they can be useful and meaningful in ED recovery.

No abstract available.

Investigative data journalists work with a variety of data sources to tell a story. Though prior work has indicated that there is a close relationship between journalists' data work practices and that of data scientists. However, these relationships and data work practices are not empirically examined, and understanding them is crucial to inform the design of tools that are used by different groups of people including data scientists and data journalists. Thus, to bridge this gap, we studied investigative reporters' data work practices with one non-profit investigative newsroom. Our study design includes two activities: 1) semi-structured interviews with journalists, and 2) a sketching activity allowing journalists to depict examples of their work practices. By analyzing these data and synthesizing them across related prior work, we propose the major phases in the data-driven investigative journalism story idea generation process. Our study findings show that the journalists employ a collection of multiple, iterative, cyclic processes to identify journalistically "interesting'' story ideas. These processes both significantly resemble and show subtle nuanced differences with data science work practices identified in prior research. We further verified our proposal through a member check with key informants. This work offers three primary contributions. First, it provides a close glimpse into the main phases of investigative journalists' data-driven story idea generation technique. Second, it complements prior work studying formal data science practices by examining data-driven investigative journalists, whose primary expertise lies outside computing. Third, it identifies particular points in the data exploration processes that would benefit from design interventions and suggests future research directions.

This paper examines volitionality of Facebook usage, that is, which individuals feel they have a choice about whether or not to use the site. It analyzes data from two large surveys, conducted three years apart. Across the two surveys, a variety of factors impacted whether or not respondents saw their Facebook usage as a matter of their own choice, such as engaging in non-use behaviors, measures of Facebook addiction, a sense of their own agency, and, across both studies, level of education. These results expand on prior literature around technology use and non-use, especially in terms of which populations may feel obligated to use, or be unwillingly prevented from using, social media such as Facebook. Furthermore, they provide potential implications both for future work and for technology policy.

Technology bears important relationships to our health and wellness and has been utilized over the past two decades as an aid to support both self-management goals as well as collaboration among treatment teams.However, when chronic illnesses such as eating disorders (ED) are managed outside of institutionalized care settings, designing effective technology to support collaboration in treatment necessitates that we understand the relationships between patients, clinicians, and support networks. We conducted in-depth, semi-structured, interviews with 9 ED patients and 10 clinicians to understand the ED journey through the lens of collaborative efforts, technology use, and potential detriments. Based on our analysis of these 19 interviews, we present novel findings on various underlying disconnects within the collaborative ED treatment process disconnects among clinicians, between treatment foci, among preferences in tracking, within support networks, and inpatients' own identities. Our findings highlight how these various disconnects are concomitant with and gaps can stem from a lack of collaboration between different stakeholders in the ED journey. We also identify methods of facilitating collaboration in these disconnects through technological mediators.

Design fiction has become so widely adopted that it regularly appears in contexts ranging from CEO speeches to dedicated tracks at academic conferences. However, evaluating this kind of work is difficult; it is not clear what good or bad design fiction is or what the judgment criteria should be. In this paper we assert that design fiction is a heterogeneous set of methods, and practices, able to produce a diversity of scholarly and design contributions. We argue locating these diverse practices under the single header of "design fiction" has resulted in epistemological confusion over the appropriate method of evaluation. We identify different traditions within the HCI literature-critical design; narratology and literary theory; studio-based design "crits"; user studies; scenarios and persona development; and thought experiments-to articulate a typology of evaluative frames. There is often a mismatch between the standards to which design fiction is held and the knowledge that speculative methods seek to produce. We argue that evaluating a given instance of design fiction requires us to properly select the right epistemological tool for the job.

Motivated by the effects of the filter bubble and echo chamber phenomena on social media, we developed a smart home device, Spkr, that unpredictably "pushes" socio-political discussion topics into the home. The device utilised trending Twitter discussions, categorised by their socio-political alignment, to present people with a purposefully assorted range of viewpoints. We deployed Spkr in 10 homes for 28 days with a diverse range of participants and interviewed them about their experiences. Our results show that Spkr presents a novel means of combating selective exposure to socio-political issues, providing participants with identifiably diverse viewpoints. Moreover, Spkr acted as a conversational prompt for discussion within the home, initiating collective processes and engaging those who would not often be involved in political discussions. We demonstrate how smart home assistants can be used as a catalyst for provocation by altering and pluralising political discussions within households.

Designing computational systems means, increasingly, designing for interactions with algorithms. Machine learning, recommender systems, sentiment analysis, and other algorithmic techniques have bec...

Prior studies of technology non-use demonstrate the need for approaches that go beyond a simple binary distinction between users and non-users. This paper proposes a set of two different methods by which researchers can identify types of non/use relevant to the particular sociotechnical settings they are studying. These methods are demonstrated by applying them to survey data about Facebook non/use. The results demonstrate that the different methods proposed here identify fairly comparable types of non/use. They also illustrate how the two methods make different trade offs between the granularity of the resulting typology and the total sample size. The paper also demonstrates how the different typologies resulting from these methods can be used in predictive modeling, allowing for the two methods to corroborate or disconfirm results from one another. The discussion considers implications and applications of these methods, both for research on technology non/use and for studying social computing more broadly.

This paper addresses challenges in conceptualizing privacy posed by algorithmic systems that can infer sensitive information from seemingly innocuous data. This type of privacy is of imminent concern due to the rapid adoption of machine learning and artificial intelligence systems in virtually every industry. In this paper, we suggest informational friction, a concept from Floridi's ethics of information, as a valuable conceptual lens for studying algorithmic aspects of privacy. Informational friction describes the amount of work required for one agent to access or alter the information of another. By focusing on amount of work, rather than the type of information or manner in which it is collected, informational friction can help to explain why automated analyses should raise privacy concerns independently of, and in addition to, those associated with data collection. As a demonstration, this paper analyze law enforcement use of facial recognition, andFacebook's targeted advertising model using informational friction and demonstrate risks inherent to these systems which are not completely identified in another popular framework, Nissenbaum's Contextual Integrity.The paper concludes with a discussion of broader implications, both for privacy research and for privacy regulation.

Computational tools can often facilitate human work by rapidly summarizing large amounts of data, especially text. Doing so delegates to such models some measure of authority to speak on behalf of those people whose data are being analyzed. This paper considers the consequences of such delegation. It draws on sociological accounts of representation and translation to examine one particular case: the application of topic modeling to blogs written by parents of children on the autism spectrum. In doing so, the paper illustrates the kinds of statements that topic models, and other computational techniques, can make on behalf of people. It also articulates some of the potential consequences of such statements. The paper concludes by offering several suggestions about how to address potential harms that can occur when computational models speak on behalf of someone.

Relatively little work has empirically examined use and non-use of social technologies as more than a dichotomous binary, despite increasing calls to do so. This paper compares three different forms of non/use that might otherwise fall under the single umbrella of Facebook "user": (1) those who have a current active account; (2) those who have deactivated their account; and (3) those who have considered deactivating but not actually done so. A subset of respondents (N=256) from a larger, demographically representative sample of internet users completed measures for usage and perceptions of Facebook, Facebook addiction, privacy experiences and behaviors, and demographics. Multinomial logistic regression modeling shows four specific variables as most predictive of a respondent's type: negative effects from "addictive" use, subjective intensity of Facebook usage, number of Facebook friends, and familiarity with or use of Facebook's privacy settings. These findings both fill gaps left by, and help resolve conflicting expectations from, prior work. Furthermore, they demonstrate how valuable insights can be gained by disaggregating "users" based on different forms of engagement with a given technology.

"Human-centered machine learning" (HCML) combines human insights and domain expertise with data-driven predictions to answer societal questions. This area's inherent interdisciplinarity causes tensions in the obligations researchers have to the humans whose data they use. This paper studies how scientific papers represent human research subjects in HCML. Using mental health status prediction on social media as a case study, we conduct thematic discourse analysis on 55 papers to examine these representations. We identify five discourses that weave a complex narrative of who the human subject is in this research: Disorder/Patient, Social Media, Scientific, Data/Machine Learning, and Person. We show how these five discourses create paradoxical subject and object representations of the human, which may inadvertently risk dehumanization. We also discuss the tensions and impacts of interdisciplinary research; the risks of this work to scientific rigor, online communities, and mental health; and guidelines for stronger HCML research in this nascent area.

It is our pleasure to welcome you to the first PACMHCI GROUP issue. For over 25 years, the GROUP research community has supported the development of robust scholarship at the intersection of Computer Supported Cooperative Work, Human Computer Interaction, Computer Supported Collaborative Learning and Socio-Technical Studies. This volume is the latest product of our efforts to validate and integrate the strong work happening within this broadly-conceived community. We hope that the range of papers presented here reflects our intent to be international, interdisciplinary, and inclusive, both in our organization of the review process as well as within the set of accepted papers. This first PACM journal volume in the GROUP series features studies of collaboration in multiple settings, including social networks, editing systems, and mixed reality. It also showcases sociotechnical studies in domains ranging from outdoor activities to scientific projects.

Use and non-use of technology can occur in a variety of forms. This paper analyzes data from a probabilistic sample of 1000 US households to identify predictors for four different types of use and non-use of the social media site Facebook. The results make three important contributions. First, they demonstrate that many demographic and socioeconomic predictors of social media use and non-use identified in prior studies hold with a larger, more diverse sample. Second, they show how going beyond a binary distinction between use and non-use reveals inequalities in social media use and non-use not identified in prior work. Third, they contribute to ongoing discussions about the representativeness of social media data by showing which populations are, and are not, represented in samples drawn from social media.

Design fiction can be highly effective at envisioning possible futures. That envisioning enables, among other things, considering ethical implications of possible technologies. This paper highlights that capacity through a curated collection of five short design fiction pieces, each accompanied by its own author statement. Spanning multiple genres, each piece highlights ethical issues in its own way. After considering the unique strategies that each piece uses to highlight ethical issues, the paper concludes with considerations of how design fiction can advance broader discussions of ethics in computing.

Previous work has explored regretful experiences on social media. In parallel, scholars have examined how people do not use social media. This paper aims to synthesize these two research areas and asks: Do regretful experiences on social media influence people to (consider) not using social media? How might this influence differ for different sorts of regretful experiences? We adopted a mixed methods approach, combining topic modeling, logistic regressions, and contingency analysis to analyze data from a web survey with a demographically representative sample of US internet users (n=515) focusing on their Facebook use. We found that experiences that arise because of users' own actions influence actual deactivation of their Facebook account, while experiences that arise because of others' actions lead to considerations of non-use. We discuss the implications of these findings for two theoretical areas of interest in HCI: individual agency in social media use and the networked dimensions of privacy.

Public concern related to a policy may span a range of topics. As a result, policy discussions struggle to deeply examine any one topic before moving to the next. In policy deliberation research, this is referred to as a problem of topical coherence. In an experiment, we curated the comments in a policy discussion to prioritize arguments for or against a policy proposal, and examined how this curation and participants' initial positions of support or opposition to the policy affected the coherence of their contributions to existing topics. We found an asymmetric interaction between participants' initial positions and comment curation: participants with different initial positions had unequal reactions to curation that foregrounded comments with which they disagreed. This asymmetry implies that the factors underlying coherence are more nuanced than prioritizing participants' agreement or disagreement. We discuss how this finding relates to curating for coherent disagreement, and for curation more generally in deliberative processes.

Recent work has identified a variety of motivations for various forms of technology use and non-use. However, less work has closely examined relationships between those motivations and the experiences of transiting among these different forms of use and non-use. This paper fills that gap by conducting a qualitative interview- and diary-based study where participants were asked to deactivate their Facebook account. An abductive analysis suggests participants' experiences can be organized under the conceptual umbrella of sense of agency, which refers to an individual's perception that their actions are under their own control. The analysis shows how, across disparate motivations, all participants took actions that increased their own subjective sense of agency, regardless of whether they returned to Facebook or not. The discussion applies this conceptual lens to prior studies of technology use and non-use. Doing so shows how sense of agency may provide an organizing orientation for understanding subjective experiences of use and non-use.

Information visualizations are often evaluated as a tool in terms of their ability to support performance of a specific task. This article argues that value can be gained by instead evaluating visualizations from a communicative perspective. Specifically, it explores how text visualization can influence the impacts that framing has on the perception of political issues. Using data from a controlled laboratory study, the results presented here demonstrate that exposure to a text visualization can mitigate framing effects. Furthermore, it also shows a transfer effect, where participants who saw the visualization remained uninfluenced by framing in subsequent texts, even when the visualization was absent. These results carry implications for the methods used to evaluate information visualization systems, for understanding the cognitive and interpretive mechanisms by which framing effects occur, and for exploring the design space of interactive text visualization.

HCI is focused on improving the interactions we have with technology and innovating new types of interactions, as well as expanding the types of people for whom those interactions are designed. Central to these efforts is the simultaneously empowering and contested construct of the "user." This paper examines what the construct of the user highlights, as well as what it conceals. We introduce post-userism, a perspective that simultaneously acknowledges the limits of, and proposes alternatives to, the central construct of the user as proxy for the "human" in HCI. Drawing on developments across the historical trajectory of HCI, we articulate how the user is enacted across four different levels of representation-systems, interface, design process, and the ideology and identify situations where the user breaks down. Synthesizing prior work, we offer a series of strategies for grappling with such situations. In doing so, we seek to overcome the limitations imposed by the user and develop a language that will aid in evolving the foundations of HCI by asking what, exactly, we place at the center of our scholarship and design.

This paper describes the use of the Delphi method as a means of incorporating study participants into the processes of data analysis and interpretation.As a case study, it focuses on perceptions about use and non-use of the social media site Facebook.The work presented here involves three phases.First, a large survey included both a demographically representative sample and a convenience sample.Second, a smaller follow-up survey presented results from that survey back to survey respondents.Third, a series of qualitative member checking interviews with additional survey respondents served to validate the findings of the follow-up survey.This paper demonstrates the utility of Delphi by highlighting the ways that it enables us to synthesize across these three study phases, advancing understanding of perceptions about social media use and non-use.The paper concludes by discussing the broader applicability of the Delphi method across CSCW research.

Researchers in information science and related areas have developed various methods for analyzing textual data, such as survey responses. This article describes the application of analysis methods from two distinct fields, one method from interpretive social science and one method from statistical machine learning, to the same survey data. The results show that the two analyses produce some similar and some complementary insights about the phenomenon of interest, in this case, nonuse of social media. We compare both the processes of conducting these analyses and the results they produce to derive insights about each method's unique advantages and drawbacks, as well as the broader roles that these methods play in the respective fields where they are often used. These insights allow us to make more informed decisions about the tradeoffs in choosing different methods for analyzing textual data. Furthermore, this comparison suggests ways that such methods might be combined in novel and compelling ways.

Grounded Theory Method (GTM) and Machine Learning (ML) are often considered to be quite different. In this note, we explore unexpected convergences between these methods. We propose new research directions that can further clarify the relationships between these methods, and that can use those relationships to strengthen our ability to describe our phenomena and develop stronger hybrid theories.

To examine the processes by which appropriation happens around an interactive art installation in an organizational context, this paper presents a qualitative, longitudinal study of an interactive art installation called mood.cloud. While designed to collect and to visually display building occupants' collective emotion, the installation was not necessarily used or interpreted in this way. Instead, building occupants saw the sensory experience of mood.cloud and the ability to change the display as a way to influence their own feelings, the feelings of others, and the overall workplace ambience. We found that interaction with mood.cloud fostered reflection about the relationship between the individual and the larger collective that the person is a part of. This relationship, between appropriation for individual benefit and appropriation for the benefit of others, afforded participants the opportunity to become more aware of their own contribution as part of a larger community. These findings suggest an opportunity to design systems around the interplay between appropriation for the individual and appropriation for the community.

Despite demonstrated interest in designing for reflection, relatively little work provides a detailed explication of what exactly is meant by reflection or how to design around it. This paper fills that gap by reviewing and engaging with conceptual and theoretical models of reflection, organized by the disciplinary and epistemological perspectives each embodies. Synthesizing across this theoretical background, the paper identifies three dimensions of reflection: breakdown, inquiry, and transformation. Together, these dimensions serve as the foundation for reflective informatics, a conceptual approach that helps bring clarity and guidance to the discussion of designing for reflection. The paper distinguishes reflective informatics by demonstrating how it both differs from and complements existing related work. Finally, the paper provides a critically reflexive consideration of its own latent assumptions, especially about the value of reflection, and how they might impact work on designing for reflection.

HCI has developed a powerful vocabulary for thinking about, and methods for engaging with, users. Similarly, recent work has advanced complementary understanding of technology non-use. However, other spaces of interaction with technology may occur that sit uncomfortably between these two poles. This paper presents two case studies highlighting individuals who neither are clearly users of a system nor are clearly non-users. Based on these cases, the paper develops the concept of usee to help account for such situations that lie between existing analytic categories.

Eric Baumer, Elisha Elovic, Ying Qin, Francesca Polletta, Geri Gay. Proceedings of the 2015 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies. 2015.

Designers have demonstrated an increased interest in designing for reflection. However, that work currently occurs under a variety of diverse auspices. To help organize and investigate this literature, this paper present a review of research on systems designed to support reflection. Key findings include that most work in this area does not actually define the concept of reflection. We also find that most evaluations do not focus on reflection per se rather but on some other outcome arguably linked to reflection. Our review also describes the relationship between reflection and persuasion evidenced implicitly by both rhetorical motivations for and implementation details of system design. After discussing the significance of our findings, we conclude with a series of recommendations for improving research on and design for reflection.

Social support plays an important role in health systems. While significant work has explored the role of social support in CMC environments, less analysis has considered social support in mobile health systems. This paper describes socially supportive messages in VERA, a mobile application for sharing health decisions and behaviors. The short and bursty interactions in social awareness streams [36] afford a particular style of social support, for which we offer the label staccato social support. Results indicate that, in comparison to previous work, staccato social support is characterized by a greater prevalence of esteem support, which builds respect and confidence. We further note the presence of 'following up', a positive behavior that contributes to supportive interactions, likely via social pressure and accountability [7,38]. These findings suggest design recommendations to developers of mobile social support systems and contribute to understanding technologically mediated social support for health.

Visual approaches for conducting research during the design process often give voice to people and ideas that might otherwise remain obscured. Recent and increasing interest in visual research techniques has coincided with technological advances such as camera phones and visually oriented mobile applications. As a result of this close association between digital technologies and image-based research techniques, there are multiple opportunities and challenges within human–computer interaction (HCI) design practice to employ these strategies to improve user experiences. This article provides an overview of current visual approaches to research highlighting the role technology has played in facilitating and inspiring these techniques. A series of case studies are presented that provide a basis for understanding a breadth of visual approaches in HCI design practices as well as serve as a point of entry to a critical and reflective discussion about the use of these approaches in different circumstances. Based on these reflections, three value statements are offered as a means to encourage the use of these visual approaches more broadly and critically in HCI design studies.

Despite the abundance of research on social networking sites, relatively little research has studied those who choose not to use such sites. This paper presents results from a questionnaire of over 400 Internet users, focusing specifically on Facebook and those users who have left the service. Results show the lack of a clear, binary distinction between use and non-use, that various practices enable diverse ways and degrees of engagement with and disengagement from Facebook. Furthermore, qualitative analysis reveals numerous complex and interrelated motivations and justifications, both for leaving and for maintaining some type of connection. These motivations include: privacy, data misuse, productivity, banality, addiction, and external pressures. These results not only contribute to our understanding of online sociality by examining this under-explored area, but they also build on previous work to help advance how we conceptually account for the sociological processes of non-use.

We present an alternative approach to the design of personal informatics systems: instead of motivating people to examine their own behaviors, this approach promotes awareness of and reflection on the infrastructures behind personal informatics and the modes of engagement that they promote. Specifically, this paper presents an interface that displays personal web browsing data. The interface aims to reveal underlying infrastructure using several methods: drawing attention to the scope of mined data by displaying deliberately selected sensitive data, using purposeful malfunction as a way to encourage reverse engineering, and challenging normative expectations around data mining by displaying information in unconventional ways. Qualitative results from a two-week deployment show that these strategies can raise people's awareness about data mining, promote efficacy and control over personal data, and inspire reflection on the goals and assumptions embedded in infrastructures for personal data analytics.

In this paper we provide a critical analysis of persuasive sustainability research from 2009-2011. Drawing on critical sociological theory of modernism, we argue that persuasion is based on a limited framing of sustainability, human behavior, and their interrelationship. This makes supporting sustainability easier, but leads to characteristic patterns of breakdown. We then detail problems that emerge from this narrowing of vision, such as how the framing of sustainability as the optimization of a simple metrics places technologies incorrectly as objective arbiters over complex issues of sustainability. We conclude by suggesting alternative approaches to move beyond these problems.

Most mobile technology systems designed to encourage healthy decisions focus on prescriptive persuasion, telling the user either implicitly or explicitly what to do, as the primary means of improving health. However, other technically and socially viable options exist. Drawing on both relevant social theory and previous CSCW research, this paper suggests that open-ended social awareness, making users aware of both others' and their own decisions, may also serve as an effective central design principle for mobile health. To explore this approach, this paper presents analysis of qualitative data from two studies of such a system. Results suggest that open-endedness allowed users flexibility and freedom in defining what counts as health, and that the social aspects compounded both the positive and the occasionally negative impacts of this openness. The paper concludes with implications for the design and evaluation of research on mobile health technology, as well as suggestions for how future work can further explore the design space of mobile health beyond prescriptive persuasion.

For many first-year college students in their late teen years, communicating with parents provides crucial social support. When going to college involves moving away from home for the first time, students and their parents must rely on technologies to keep communication channels open. We studied the ways in which college freshmen communicate with their parents and the various communication technologies they use. Interviews with nineteen first-year students at a major United States university revealed insights into students' perspectives of their communication and relationships with parents. We found students to use a variety of tools to connect with their parents and identified some considerations they make when choosing tools. Furthermore, the use of these communication tools played a significant role in mediating students' social and emotional closeness with, and independence from, their parents. We conclude by discussing technical and social implications for social support of students and student-parent relationships.

As HCI is applied in increasingly diverse contexts, it is important to consider situations in which computational or information technologies may be less appropriate. This paper presents a series of questions that can help researchers, designers, and practitioners articulate a technology's appropriateness or inappropriateness. Use of these questions is demonstrated via examples from the literature. The paper concludes with specific arguments for improving the conduct of HCI. This paper provides a means for understanding and articulating the limits of HCI technologies, an important but heretofore under-explored contribution to the field.

The field of HCI is growing, not only in the variety of application areas or the volume of research conducted, but also in the number of analytical approaches for use in the evaluation and design of interactive systems. However, despite the abundance of theoretical frameworks available, relatively little work has directly compared the application of these frameworks. This paper compares video analysis methods based on two analytic frameworks - activity theory (AT) and distributed cognition (DCog) - by performing an analysis of the same system from each of the two different theoretical perspectives. The results presented here provide a better understanding of how such theoretically informed methods in practice both resemble and differ from one another. Furthermore, this comparison enables specific insights about each of the theories themselves, as well as more general discussion about the role of theory in HCI.

In this paper we describe MoBoogie, an application that allows users to manipulate and arrange music through movement. MoBoogie is designed to foster experiences in creative expression for children and potentially adults. The application responds to users' movements by changing variables in a continuous stream of music loops. Results from this study suggest that the creative expressions arose in the joint space of movement and music, and did not primarily have to be in one form or the other. This allowed users with limited experience in dance and music making to be creative in such forms of expression.

A significant amount of research has focused on blogs, bloggers, and blogging. However, relatively little work has examined blog readers, their interactions with bloggers, or their impact on blogging. This paper presents a qualitative study focusing specifically on readers of political blogs to develop a better understanding of readers’ interactions with blogs and bloggers. This is the first such study to examine the same blogging activity from both readers’ and bloggers’ perspectives. Readers’ significance and contributions to blogs are examined through a number of themes, including: community membership and participation; the relationship between political ideology, reading habits, and political participation; and differences and similarities between mainstream media (MSM) and blogs. Based on these analyses, this paper argues that blogging is not only a social activity, but is a collaborative process of co-creation in which both bloggers and readers engage. Implications of this finding contribute to the study and understanding of reader participation, to the design of technologies for bloggers and blog readers, and to the development of theoretical understandings of social media.

Blogs are becoming an increasingly important medium -- socially, academically, and politically. Much research has involved analyzing blogs, but less work has considered how such analytic techniques might be incorporated into tools for blog readers. A new tool, metaViz, analyzes political blogs for potential conceptual metaphors and presents them to blog readers. This paper presents a study exploring the types of critical and creative thinking fostered by metaViz as evidenced by user comments and discussion on the system. These results indicate the effectiveness of various system features at fostering critical thinking and creativity, specifically in terms of deep, structural reasoning about metaphors and creatively extending existing metaphors. Furthermore, the results carry broader implications beyond blogs and politics about exploring alternate configurations between computation and human thought.

This paper investigates the work of creating infrastructure, using as a case study the development of cyberinfrastructure for metagenomics research. Specifically, the analysis focuses on the role of embeddedness in infrastructure development. We expand on the notion of human infrastructure to develop the concepts of synergizing , leveraging, and aligning, which denote the active processes of creating and managing relationships among people, organizations, and technologies in the creation of cyberinfrastructure. This conceptual lens highlights how embeddedness is not only an important result of infrastructure development, but is also a precursor that can act as both a constraint and a resource for development activities.

Metaphor is often seen as a mode of creative thinking or as a means of fostering creativity. However, little work has studied creative generation of novel metaphors. This paper explores the use of computational metaphor identification (CMI) to foster creative generation of novel metaphors. CMI is a technique for analyzing textual corpora to identify potential conceptual metaphors. Drawing those metaphors to readers' attention can provide an opportunity to consider alternatives to current metaphors. This paper describes results from a study using CMI to foster metaphorical creativity in the context of science education. The results show that CMI leads to more creative mappings within metaphors. The key contributions of this paper are a demonstration that CMI can be used to foster more original metaphorical reasoning, and, more generally, implications for the study of metaphorical creativity.

Within the last decade, blogs have become an important element of popular culture, mass media, and the daily lives of countless Internet users. Despite the medium's interactive nature, most research on blogs focuses on either the blog itself or the blogger, rarely if at all focusing on the reader's impact. In order to gain a better understanding of the social practice of blogging, we must take into account the role, contributions, and significance of the reader. This paper presents the findings of a qualitative study of blog readers, including common blog reading practices, some of the dimensions along which reading practices vary, relationships between identity presentation and perception, the interpretation of temporality, and the ways in which readers feel that they are a part of the blogs they read. It also describes similarities to, and discrepancies with, previous work, and suggests a number of directions and implications for future work on blogging.