bluuebunny/crossref_metadata_2025 huggingface dataset:
"Do You Ladies Relate?": Experiences of Gender Diverse People in Online Eating Disorder Communities
Authors: Feuston Jessica L. , DeVito Michael Ann , Scheuerman Morgan Klaus , Weathington Katy , Benitez Marianna , Perez Bianca Z. , Sondheim Lucy , Brubaker Jed R.
Published: November 2022

The study of eating disorders online has a long tradition within CSCW and HCI scholarship. Research within this body of work highlights the types of content people with eating disorders post as well as the ways in which individuals use online spaces for acceptance, connection, and support. However, despite nearly a decade of research, online eating disorder scholarship in CSCW and HCI rarely accounts for the ways gender shapes online engagement. In this paper, we present empirical results from interviews with 14 trans people with eating disorders. Our findings illustrate how working with gender as an analytic lens allowed us to produce new knowledge about the embodiment of participation in online eating disorder spaces. We show how trans people with eating disorders use online eating disorder content to inform and set goals for their bodies and how, as gender minorities within online eating disorder spaces, trans people occupy marginal positions that make them more susceptible to harms, such as threats to eating disorder validity and gender authenticity. In our discussion, we consider life transitions in the context of gender and eating disorders and address how online eating disorder spaces operate as social transition machinery. We also call attention to the labor associated with online participation as a gender minority within online eating disorder spaces, outlining several design recommendations for supporting the ways trans people with eating disorders use online spaces. CONTENT WARNING: This paper is about the online experiences of trans people with eating disorders. We discuss eating disorders, related content (e.g., thinspiration) and practices (e.g., binge eating, restriction), and gender dysphoria. Please read with caution.
Alexa as an Active Listener: How Backchanneling Can Elicit Self-Disclosure and Promote User Experience
Authors: Cho Eugene , Motalebi Nasim , Sundar S. Shyam , Abdullah Saeed
Published: November 2022

Active listening is a well-known skill applied in human communication to build intimacy and elicit self-disclosure to support a wide variety of cooperative tasks. When applied to conversational UIs, active listening from machines can also elicit greater self-disclosure by signaling to the users that they are being heard, which can have positive outcomes. However, it takes considerable engineering effort and training to embed active listening skills in machines at scale, given the need to personalize active-listening cues to individual users and their specific utterances. A more generic solution is needed given the increasing use of conversational agents, especially by the growing number of socially isolated individuals. With this in mind, we developed an Amazon Alexa skill that provides privacy-preserving and pseudo-random backchanneling to indicate active listening. User study (N = 40) data show that backchanneling improves perceived degree of active listening by smart speakers. It also results in more emotional disclosure, with participants using more positive words. Perception of smart speakers as active listeners is positively associated with perceived emotional support. Interview data corroborate the feasibility of using smart speakers to provide emotional support. These findings have important implications for smart speaker interaction design in several domains of cooperative work and social computing.
Care Frictions: A Critical Reframing of Patient Noncompliance in Health Technology Design
Authors: Burgess Eleanor R. , Kaziunas Elizabeth , Jacobs Maia
Published: November 2022

Patient work encompasses a challenging set of activities necessary for learning about and managing chronic conditions over time. Many patient-centered health technology interventions focus on supporting types of patient work, such as symptom tracking, medication adherence, and information sharing between patients and providers. However, people may not always follow, or may actively resist, the activities prescribed by their formal patient role. In this paper, we present three case studies about patients with different chronic conditions to critically reflect on the types of patient behavior commonly taken up in health technology design as acts of "noncompliance." Detailing conflicts that emerge when patients are caught between meeting their personal needs and following clinical best practices, we show how everyday life and health system goals are often misaligned in ways that can't be easily reconciled through current design approaches. As a way forward, we argue for alternative ways of understanding the tensions routinely shaping people's healthcare experiences. We introduce the term care frictions as a sensitizing concept useful for helping designers reframe "noncompliant" behaviors as legitimate forms of patient work. Our paper also offers design considerations-both on challenges and generative possibilities-for future CSCW research seeking to support a wider breadth of patient behavior. In this, we call attention to the value of designer and researcher reflexivity in making visible the problematic assumptions in health technology design that can lead to social and emotional patient harms.
Channeling End-User Creativity: Leveraging Live Streaming for Distributed Collaboration in Indie Game Development
Authors: Li Lingyuan , Freeman Guo , McNeese Nathan J.
Published: November 2022

This paper explores the role of live streaming in distributed collaborative software development using indie game development, an end-user driven creative community, as an example. We conducted 27 in-depth interviews with indie game developers from various cultures and countries, who had engaged in live streaming for collaborative software development either as a streamer or a viewer. Our findings show how live streaming can be used by indie game developers to support their endeavors to innovate the traditional game development model, which goes beyond just learning and teaching technical skills. We also highlight the potential challenges indie developers face in this process. We thus make unique contributions to CSCW by bridging the previously often disconnected research agendas on collaborative software development and live streaming. We also provide potential directions for designing future live streaming platforms to better support distributed collaboration in emerging end-user driven creative activities.
Characterizing Alternative Monetization Strategies on YouTube
Authors: Hua Yiqing , Horta Ribeiro Manoel , Ristenpart Thomas , West Robert , Naaman Mor
Published: November 2022

One of the key emerging roles of the YouTube platform is providing creators the ability to generate revenue from their content and interactions. Alongside tools provided directly by the platform, such as revenue-sharing from advertising, creators co-opt the platform to use a variety of off-platform monetization opportunities. In this work, we focus on studying and characterizing these alternative monetization strategies. Leveraging a large longitudinal YouTube dataset of popular creators, we develop a taxonomy of alternative monetization strategies and a simple methodology to detect their usage automatically. We then proceed to characterize the adoption of these strategies. First, we find that the use of external monetization is expansive and increasingly prevalent, used in 18% of all videos, with 61% of channels using one such strategy at least once. Second, we show that the adoption of these strategies varies substantially among channels of different kinds and popularity, and that channels that establish these alternative revenue streams often become more productive on the platform. Lastly, we investigate how potentially problematic channels -- those that produce Alt-lite, Alt-right, and Manosphere content -- leverage alternative monetization strategies, finding that they employ a more diverse set of such strategies significantly more often than a carefully chosen comparison set of channels. This finding complicates YouTube's role as a gatekeeper, since the practice of excluding policy-violating content from its native on-platform monetization may not be effective. Overall, this work provides an important step toward broadening the understanding of the monetary incentives behind content creation on YouTube.
CrowdNAS: A Crowd-guided Neural Architecture Searching Approach to Disaster Damage Assessment
Authors: Zhang Yang , Zong Ruohan , Kou Ziyi , Shang Lanyu , Wang Dong
Published: November 2022

Disaster damage assessment (DDA) has emerged as an important application in disaster response and management, which aims to assess the damage severity of an affected area by leveraging AI (e.g., deep learning) techniques to examine the imagery data posted on social media during a disaster event. In this paper, we focus on a crowd-guided neural architecture searching (NAS) problem in DDA applications. Our goal is to leverage human intelligence from crowdsourcing systems to guide the discovery of the optimal neural network architecture in the design space to achieve the desirable damage assessment performance. Our work is motivated by the limitation that the deep neural network architectures in current DDA solutions are mainly designed by AI experts, which is known to be both time-consuming and error-prone. Two critical technical challenges exist in solving our problem: i) it is challenging to design a manageable NAS space for crowd-based solutions; ii) it is non-trivial to transfer the imperfect crowd knowledge to effective decisions in identifying the optimal neural network architecture of a DDA application. To address the above challenges, we develop CrowdNAS, a crowd-guided NAS framework that develops novel techniques inspired by AI, crowdsourcing, and estimation theory to address the NAS problem. The evaluation results from two real-world DDA applications show that CrowdNAS consistently outperforms the state-of-the-art AI-only, crowd-AI, and NAS baselines by achieving the highest classification accuracy in the damage assessment while maintaining a low computational cost under various evaluation scenarios.
Designing a Data Story: A Storytelling Approach to Curation, Sharing and Data Reuse in Support of Ethnographically-driven Research
Authors: Mosconi Gaia , Randall Dave , Karasti Helena , Aljuneidi Saja , Yu Tong , Tolmie Peter , Pipek Volkmar
Published: November 2022

In this paper, we introduce an innovative design concept for the curation of data, which we call 'Data Story'. We view this as an additional resource for data curation, aimed specifically at supporting the sharing of qualitative and ethnographic data. The Data Story concept is motivated by three elements: 1. the increased attention of funding agencies and academic institutions on Research Data Management and Open Science; 2. our own work with colleagues applying ethnographic research methods; and 3. existing literature that has identified specific challenges in this context. Ongoing issues entailed in dealing with certain contextual factors that are inherent to qualitative research reveal the extent to which we still lack technical design solutions that can support meaningful curation and sharing. Data Story provides a singular way of addressing these issues by integrating traditional data curation approaches, where research data are treated as 'objects' to be curated and preserved according to specific standards, with a more contextual, culturally-nuanced and collaborative organizing layer that can be thought of as a "Story". The concept draws on existing literature on data curation, digital storytelling and Critical Data Studies (CDS). As a possible design solution for Research Data Management and data curation, Data Story offers: 1) a collaborative workflow for data curation; 2) a story-like format that can serve as an organizing principle; 3) a means of enhancing and naturalizing curation practices through storytelling. Data Story is currently being developed for deployment and evaluation.
Designing for Shared Values: Exploring Ethical Dilemmas of Conducting Values Inclusive Design Research
Authors: Jonas Rebecca M. , Hanrahan Benjamin V.
Published: November 2022

Recent prevalence of values-inclusive design research introduces the potential of conducting research with those whose values conflict with researchers' own values. This is the scenario we have found ourselves in as we conduct values-inclusive participatory design to develop and deploy critical digital literacy education in a rural Appalachian community. We present provocations which outline the ethical concerns we have grappled with in pursuit of conducting fair and responsible research for our participants, indirect stakeholders, and ourselves. Through consideration of these provocations, we have developed a preliminary approach for managing a research relationship with those with whom we disagree which we call Designing for Shared Values. This approach is a conflict-avoidant method for negotiating values in values-inclusive design. It centers around reflexivity as a mechanism to account for one's own values and potential impacts of design research outcomes on indirect stakeholders, while maintaining responsibility to prioritize beneficial outcomes to research participants.
Destructive Criticism in Software Code Review Impacts Inclusion
Authors: Gunawardena Sanuri Dananja , Devine Peter , Beaumont Isabelle , Garden Lola Piper , Murphy-Hill Emerson , Blincoe Kelly
Published: November 2022

The software industry lacks gender diversity. Recent research has suggested that a toxic working culture is to blame. Studies have found that communications in software repositories directed towards women are more negative in general. In this study, we use a destructive criticism lens to examine gender differences in software code review feedback. Software code review is a practice where code is peer reviewed and negative feedback is often delivered. We explore differences in perceptions, frequency, and impact of destructive criticism across genders. We surveyed 93 software practitioners eliciting perceived reactions to hypothetical scenarios (or vignettes) where participants are asked to imagine receiving either constructive or destructive criticism. In addition, the survey collected general opinions on feedback obtained during software code review as well as the frequency that participants give and receive destructive criticism.

We found that opinions on destructive criticism vary. Women perceive destructive criticism as less appropriate and are less motivated to continue working with the developer after receiving destructive criticism. Destructive criticism is fairly common with more than half of respondents having received nonspecific negative feedback and nearly a quarter having received inconsiderate negative feedback in the past year. Our results suggest that destructive criticism in code review could be a contributing factor to the lack of gender diversity observed in the software industry.
Do as I say, not as I do: Therapist Evaluation of a Practice and Supervision Aid
Authors: Kuo Patty Beyrong , Soma Christina , Axford Katherine , Hirsch Tad , Imel Zac E. , Van Epps Jake J.
Published: November 2022

Interactive software offers the potential to improve the quality of mental health care by promoting skill development, clinical insight, and shared reflection among mental health professionals. However, research on therapists' usage of interactive software has been primarily based in training and mock-clinical settings. In this paper, we present a qualitative study of clinicians' experience using CORE-MI, a collaborative recording and annotation software, in a real-world university counseling center. We describe how and why therapists, both trainees and licensed staff, used CORE-MI to support their practice and improve their skills. We also consider how usage varied with therapists' developmental level and how the software impacted relationships between supervisors and supervisees. Finally, we offer recommendations for future research and design of interactive systems in mental health settings.
Family Care Coordination in the Children's Hospital: Phases and Cycles in the Pediatric Cancer Caregiving Journey
Authors: Nikkhah Sarah , John Swaroop , Yalamarti Krishna Supradeep , Mueller Emily L. , Miller Andrew D.
Published: November 2022

When a child is hospitalized with a serious illness, their family members must process emotional stress, quickly absorb complicated clinical information, and take on new caregiving tasks. They also have to coordinate with each other and with other family caregivers without abandoning existing work and home life responsibilities. Previous CSCW and HCI research has shown how the patient's experience changes across the illness journey, but less is known about the effect of this journey on family caregivers and their coordination work. CSCW technologies could support and augment family care coordination work across the journey, reducing stress levels and improving families' ability to stay connected and informed. In this paper, we report findings from an interview study we conducted with 14 parents of children undergoing extended hospitalization for cancer treatment. We propose the concept of caregiving coordination journeys and describe caregivers' current communication and coordination practices across different phases of the hospitalization journey, from diagnosis and early hospitalization to extended hospitalization and beyond. We characterize families' caregiving coordination routines across different time scales, and describe the current role of communication technologies in families' coordination practices. We then propose design opportunities for social computing technologies to support and augment families' communication and caregiving work during the hospitalization journey of their child.
Information Needs of Essential Workers During the COVID-19 Pandemic
Authors: Aubin Le Quéré Marianne , Chiang Ting-Wei , Levy Karen , Naaman Mor
Published: November 2022

COVID-19 has been a sustained and global crisis with a strong continual impact on daily life. Staying accurately informed about COVID-19 has been key to personal and communal safety, especially for essential workers---individuals whose jobs have required them to go into work throughout the pandemic---as their employment has exposed them to higher risks of contracting the virus. Through 14 semi-structured interviews, we explore how essential workers across industries navigated the COVID-19 information landscape to get up-to-date information in the early months of the pandemic. We find that essential workers living through a sustained crisis have a broad set of information needs. We summarize these needs in a framework that centers 1) fulfilling job requirements, 2) assessing personal risk, and 3) keeping up with crisis news coverage. Our findings also show that the sustained nature of COVID-19 crisis coverage led essential workers to experience breaking points and develop coping strategies. Additionally, we show how workplace communications may act as a mediating force in this process: lack of adequate information in the workplace caused workers to struggle with navigating a contested information landscape, while consistent updates and information exchanges at work could ease the stress of information overload. Our findings extend the crisis informatics field by providing contextual knowledge about the information needs of essential workers during a sustained crisis.
Matching for Peer Support: Exploring Algorithmic Matching for Online Mental Health Communities
Authors: Fang Anna , Zhu Haiyi
Published: November 2022

Online mental health communities (OMHCs) have emerged in recent years as an effective and accessible way to obtain peer support, filling crucial gaps of traditional mental health resources. However, the mechanisms for users to find relationships that fulfill their needs and capabilities in these communities are highly underdeveloped. Using a mixed-methods approach of user interviews and behavioral log analysis on 7Cups.com, we explore central challenges in finding adequate peer relationships in online support platforms and how algorithmic matching can alleviate many of these issues. We measure the impact of using qualities like gender and age in purposeful matching to improve member experiences, with especially salient results for users belonging to vulnerable populations. Lastly, we note key considerations for designing matching systems in the online mental health context, such as the necessity for better moderation to avoid potential harassment behaviors exacerbated by algorithmic matching. Our findings yield key insights into current user experiences in OMHCs as well as design implications for building matching systems in the future for OMHCs.
Meeting Young Adults' Social Support Needs across the Health Behavior Change Journey: Implications for Digital Mental Health Tools
Authors: Meyerhoff Jonah , Kornfield Rachel , Mohr David C. , Reddy Madhu
Published: November 2022

In pursuit of mental wellness, many find that behavioral change is necessary. This process can often be difficult but is facilitated by strong social support. This paper explores the role of social support across behavioral change journeys among young adults, a group at high risk for mental health challenges, but with the lowest rates of mental health treatment utilization. Given that digital mental health tools are effective for treating mental health conditions, they hold particular promise for bridging the treatment gap among young adults, many of whom, are not interested in - or cannot access - traditional mental healthcare. We recruited a sample of young adults with depression who were seeking information about their symptoms online to participate in an Asynchronous Remote Community (ARC) elicitation workshop. Participants detailed the changing nature of social interactions across their behavior change journeys. They noted that both directed and undirected support are necessary early in behavioral change and certain needs such as informational support are particularly pronounced, while healthy coping partnerships and accountability are more important later in the change process. We discuss the conceptual and design implications of our findings for the next generation of digital mental health tools.
Nationalizing the Internet to Break a Protest Movement: Internet Shutdown and Counter-Appropriation in Iran of Late 2019
Authors: Grinko Margarita , Qalandar Sarvin , Randall Dave , Wulf Volker
Published: November 2022

To deal with a spontaneous civil uprising following a substantial rise in gas prices, the Iranian security apparatus imposed in late 2019 techno-political measures and blocked access to international websites and services. To analyze these measures, we conducted 19 interviews with Iranians living inside and outside the country. We argue that the concept of the shutdown, as portrayed in Western media, is not perfectly suitable to describe the infrastructural restrictions and propose the concept of an internet nationalization. This paper offers an in-depth analysis of what the nationalization meant and how it affected the lives of Iranians participating or not participating in the protests. We also report on a variety of creative measures, both technical and non-technical, Iranians took to counter-appropriate the government-imposed shutdown of international connectivity. Based on these data, we elaborate on the concept of counter-appropriation.
Shame on Who? Experimentally Reducing Shame During Political Arguments on Twitter
Authors: Baughan Amanda , Cross Katherine Alejandra , Khasanova Elena , Hiniker Alexis
Published: November 2022

Online political arguments have a reputation for being futile exchanges, partially because people often respond more punitively to those who do not share their views, a phenomenon called ingroup bias. We explore how ingroup bias affects political disagreements online, and how respect can mitigate its effects. Towards this goal, we conducted an experiment on Twitter systematically varying respectful versus neutral disagreement language across people who did and did not share views. We found that people who do not share views were most likely to reply to disagreements, and neutral disagreements generated more discussions than respectful disagreements. However, we also found that using respectful language increased respectful language received in return, and it reduced the effects of ingroup bias across conversations with people who do and do not share the same views. We conclude with recommendations to promote respectful language on social media and build shame resiliency online, such as designs that encourages thoughtful engagement and a peer support network that allows users to share shame experiences online.
Social Media's Role During Identity Changes Related to Major Life Events
Authors: Corvite Shanley , Zhang Ben Zefeng , Haimson Oliver L.
Published: November 2022

Major life events can cause great upheaval in one's life. Many people perceive their identities to change due to major life events. During identity shifts, impression management and self-presentation, online communities, and social media affordances can allow individuals to better facilitate their experiences. To examine how people perceive their identity to change during major events and how they use social media in the process, we interviewed 28 participants who recently experienced major life events. We found that many people perceived their identity to change through various avenues that they felt were important to their identity: mental processes, identity roles, and identity fulfillment. However, some people perceive their identity to be maintained rather than changed. During identity changes or maintenance, participants utilized impression management and self-presentation to curate their online presence. Participants also used online communities to build relationships with similar others or virtual friends and enable more connections via what we call the domino effect. Social media sites also provided the affordances of editability, visibility control, and spreadability, which can help ease life transition and identity change processes.
Territoriality in Hybrid Collaboration
Authors: Neumayr Thomas , Augstein Mirjam , Kubicek Bettina
Published: November 2022

Hybrid Collaboration, where remote and co-located team members work together using different devices and tools, has already been trending in recent years (e.g., through globalization and international cooperation) but experienced a further boost since the outbreak of the COVID-19 pandemic. The reason behind this surge in hybrid practices is probably that the crisis revealed aspects of remote collaboration which proved functional and which many decision makers (in industry as well as academia) plan to retain for the future. Thus, hybrid collaboration is an extremely timely topic which should be further studied in the context of CSCW. One major CSCW-anchored concept that has most intensively been researched in co-located collaboration settings where it is usually inherently related to spatial aspects and proximity, is territoriality. Already work on territoriality in fully distributed, remote settings has shown that there are significant differences due to the characteristics of the scenario. In this paper, we focus on territoriality in hybrid settings where we identified a significant research gap, and present the results of a user study with 22 teams consisting of four people each (distributed across two locations at two different universities), collaborating on a problem-solving task. Our findings reveal that more dimensions and communication channels, in addition to space, might strongly impact territoriality and territorial behavior in hybrid collaboration. Besides classical spatial territories also auditory territories frequently emerged. In addition, visibility of and accessibility to certain territories need to be rethought. We discuss these novel findings also regarding their interplay with earlier ones and derive design implications for CSCW systems supporting hybrid collaboration.
The Risks, Benefits, and Consequences of Prepublication Moderation: Evidence from 17 Wikipedia Language Editions
Authors: Tran Chau , Champion Kaylea , Hill Benjamin Mako , Greenstadt Rachel
Published: November 2022

Many online communities rely on postpublication moderation where contributors-even those that are perceived as being risky-are allowed to publish material immediately and where moderation takes place after the fact. An alternative arrangement involves moderating content before publication. A range of communities have argued against prepublication moderation by suggesting that it makes contributing less enjoyable for new members and that it will distract established community members with extra moderation work. We present an empirical analysis of the effects of a prepublication moderation system called FlaggedRevs that was deployed by several Wikipedia language editions. We used panel data from 17 large Wikipedia editions to test a series of hypotheses related to the effect of the system on activity levels and contribution quality. We found that the system was very effective at keeping low-quality contributions from ever becoming visible. Although there is some evidence that the system discouraged participation among users without accounts, our analysis suggests that the system's effects on contribution volume and quality were moderate at most. Our findings imply that concerns regarding the major negative effects of prepublication moderation systems on contribution quality and project productivity may be overstated.
Bridging the Social Distance: Offline to Online Social Support during the COVID-19 Pandemic
Authors: Hoefer Gabriela , Massachi Talie , Xu Neil G. , Nugent Nicole , Huang Jeff
Published: November 2022

The severe impact of COVID-19 in the United States has forced many students to replace in-person socialization with online digital contact. In this study, we investigate the mental health impacts associated with this shift by examining properties of online interactions that may affect loneliness and perceived social support. Students were surveyed (N=827) across 97 universities across the US during their first full semester impacted by the COVID-19 pandemic (Fall 2020). Private online interactions (messaging, phone call, video call) were found to have a comparable correlation to social support as face-to-face interactions, but public online interactions (social media) were associated with more negative outcomes. Among private platforms, messaging had the strongest correlation with social support; and daily self-disclosure over messaging yielded social support levels that were 1.21x higher than rarely or never disclosing over this platform. We speculate that factors such as the level of privacy and peoples' feelings of control contributed to disclosure and perceived social support in online platforms.
Collectives and Their Artifact Ecologies
Authors: Korsgaard Henrik , Lyle Peter , Saad-Sulonen Joanna , Klokmose Clemens Nylandsted , Nouwens Midas , Bødker Susanne
Published: November 2022

Computing today happens across multiple devices, applications, users, organizational units, and in the rest of the world outside. Groups and communities come together for different reasons and operate within contexts that may differ from dominant modes of production and consumption. With a foundation in activity theoretical HCI, we develop the concept of collective artifact ecologies. This concept enables us to identify struggles of collective use of computational devices today, delimiting collective artifact ecologies in order to study and explain how they develop and overlap. Through an analysis of three empirical cases, we illustrate the notion of collectives and how they face challenges in establishing, maintaining and negotiating their artifact ecologies. This paper, therefore, contributes a theoretical foundation for analyzing groups and communities as collectives, with a particular emphasis on the multiple tools and artifacts they use. To serve as a starting point for further engagement with these concepts, we provide guiding questions to support the understanding of collective artifact ecologies.
ColorCook: Augmenting Color Design for Dashboarding with Domain-Associated Palettes
Authors: Shi Yang , Chen Siji , Liu Pei , Long Jiang , Cao Nan
Published: November 2022

Visualization dashboards serve as an information presentation that uses a tiled layout of key metrics visualized in charts for collaborative decision-making. Existing work has developed tools and techniques for computational color design. Much of these efforts have focused on selecting effective color palettes for independent charts while few attempts have been made to support the expressive color design of multiple coordinated charts in dashboards. In this work, we describe ColorCook, an interactive system that helps design expressive and effective dashboard colorings using domain-associated palettes. ColorCook employs an integrated color workflow for dashboarding, consisting of color selection, assignment, and adjustment. We evaluated ColorCook through a crowdsourcing experiment and a user study. The results of our evaluation indicated that ColorCook is useful for effective and expressive color design.
CrowdOptim: A Crowd-driven Neural Network Hyperparameter Optimization Approach to AI-based Smart Urban Sensing
Authors: Zhang Yang , Zong Ruohan , Shang Lanyu , Kou Ziyi , Zeng Huimin , Wang Dong
Published: November 2022

AI-based smart urban sensing (ASUS) has emerged as a scalable and pervasive application paradigm in smart city planning and management that aims to automatically assess the physical status of the urban environments by leveraging AI techniques and massive urban sensing data. In this paper, we focus on a crowd-driven neural network (NN) hyperparameter optimization problem in ASUS applications. Our goal is to utilize the human intelligence from crowdsourcing systems to identify the optimal NN hyperparameter configuration for an ASUS model. Our work is motivated by the observation that the hyperparameters of current ASUS models are often manually configured by the AI specialists, which is known to be both error-prone and suboptimal. Two key technical challenges exist in solving our problem: i) it is challenging to effectively translate the highly complex NN hyperparameter optimization problem in AI to a simplified problem that can be solved by crowd workers without extensive AI expertise; ii) it is difficult to identify the optimal hyperparameter configuration in the large hyperparameter search space given the blackbox nature of the AI model. To address the above challenges, we develop CrowdOptim, a crowd-AI collaborative learning framework that integrates the techniques from crowdsourcing, hyperparameter optimization, and estimation theory to address the crowd-driven NN hyperparameter optimization problem in ASUS applications. The evaluation results from two real-world ASUS applications (i.e., smart city infrastructure monitoring (SCIM) and urban environment cleanliness assessment (UECA)) show that CrowdOptim consistently outperforms the state-of-the-art deep convolutional networks, crowd-AI, and hyperparameter optimization baselines in achieving the ASUS application objectives under various evaluation scenarios.
From Crowd Ratings to Predictive Models of Newsworthiness to Support Science Journalism
Authors: Nishal Sachita , Diakopoulos Nicholas
Published: November 2022

The scale of scientific publishing continues to grow, creating overload on science journalists who are inundated with choices for what would be most interesting, important, and newsworthy to cover in their reporting. Our work addresses this problem by considering the viability of creating a predictive model of newsworthiness of scientific articles that is trained using crowdsourced evaluations of newsworthiness. We proceed by first evaluating the potential of crowd-sourced evaluations of newsworthiness by assessing their alignment with expert ratings of newsworthiness, analyzing both quantitative correlations and qualitative rating rationale to understand limitations. We then demonstrate and evaluate a predictive model trained on these crowd ratings together with arXiv article metadata, text, and other computed features. Based on the crowdsourcing protocol we developed, we find that while crowdsourced ratings of newsworthiness often align moderately with expert ratings, there are also notable differences and divergences which limit the approach. Yet despite these limitations we also find that the predictive model we built provides a reasonably precise set of rankings when validated against expert evaluations (P@10 = 0.8, P@15 = 0.67), suggesting that a viable signal can be learned from crowdsourced evaluations of newsworthiness. Based on these findings we discuss opportunities for future work to leverage crowdsourcing and predictive approaches to support journalistic work in discovering and filtering newsworthy information.
How Background Images Impact Online Incivility
Authors: Park Jinkyung , Singh Vivek K.
Published: November 2022

Despite the potential of online spaces for the democratic development of public discourse, concerns over aggressive and uncivil interactions in those spaces are rising. Online incivility is the term to define the features of a discussion that convey an unnecessarily disrespectful tone toward the participants or the topic. Concerning the adverse impact of online incivility on users, we sought to explore ways to reduce online incivility to promote secure and trustworthy online debate culture. Meanwhile, the web is becoming increasingly multimodal and images are known to be an effective way of improving emotions. The broaden-and-build theory of positive emotions suggests that positive emotions generated by positive images can impact incivility levels. Hence, with the goal to reduce online incivility, we conducted a one factorial between-subject online experiment with three conditions (N = 105). We compared the three conditions (with a positive background image in color, a positive background image in grayscale, and no background image) to identify an efficient way of reducing online incivility. The data gathered from surveys and participants' online comments were qualitatively and quantitatively analyzed to answer the research questions. The results showed that not only positive backgrounds in color but also positive backgrounds in grayscale may be effective in reducing online incivility. The results will pave way for designing more civil discussion platforms in online settings.
Making a Radical Misogynist
Authors: Habib Hussam , Srinivasan Padmini , Nithyanand Rishab
Published: November 2022

The algorithms and the interactions facilitated by online platforms have been used by radical groups to recruit vulnerable individuals to their cause. This has resulted in the sharp growth of violent events and deteriorating online discourse. The Manosphere, a collection of radical anti-feminist communities, is one such group that has attracted attention due to its rapid growth and increasingly violent real-world outbursts. In this paper, we examine the social engagements between Reddit users who have participated in feminist discourse and the Manosphere communities on Reddit to understand the process of development of traits associated with the adoption of extremist ideologies. By using existing research on the psychology of radicalization we track how specific types of social engagement with the Manosphere influence the development of traits associated with radicalization. Our findings show that: (1) participation, even by the simple act of joining the Manosphere, has a significant influence on the language and outlook traits of a user, (2) Manosphere elites are extremely effective propagators of radical traits and cause their increase even outside the Manosphere, and (3) community perception can heavily influence a user's behavior. Finally, we examine how our findings can help draft community and platform moderation policies to help mitigate the problem of online radicalization.
Robots as a Place for Socializing
Authors: Cheon EunJeong , Schneiders Eike , Diekjobst Kristina , Skov Mikael B.
Published: November 2022

Introducing robots in the workplace entails new practices and configurations at the individual, organizational, and social levels. Prior work has focused on how robots may have an immediate effect on individual employees or tasks rather than collectively influencing employees or the organizations they work for gradually over time. By drawing on fourteen in-situ interviews with six collaborative robot (cobot) operators at a Danish manufacturing company, this paper investigates how cobots in the manufacturing context may engage broader interactions beyond the robot-operator interaction. Our focus includes spatial configurations centering around the cobots, social interactions between employees, and information flow through, within, and outside the production cells. Introducing and implementing cobots in the workplace has social dynamics at its core, which we explore in depth. This paper argues that the design of cobots and the environment around them should accommodate the possibility of more complicated social and organizational changes brought about by these robots. Lastly, we discuss research and design implications for the future of workplaces involving robots.
The Effects of AI-based Credibility Indicators on the Detection and Spread of Misinformation under Social Influence
Authors: Lu Zhuoran , Li Patrick , Wang Weilong , Yin Ming
Published: November 2022

Misinformation on social media has become a serious concern. Marking news stories with credibility indicators, possibly generated by an AI model, is one way to help people combat misinformation. In this paper, we report the results of two randomized experiments that aim to understand the effects of AI-based credibility indicators on people's perceptions of and engagement with the news, when people are under social influence such that their judgement of the news is influenced by other people. We find that the presence of AI-based credibility indicators nudges people into aligning their belief in the veracity of news with the AI model's prediction regardless of its correctness, thereby changing people's accuracy in detecting misinformation. However, AI-based credibility indicators show limited impacts on influencing people's engagement with either real news or fake news when social influence exists. Finally, it is shown that when social influence is present, the effects of AI-based credibility indicators on the detection and spread of misinformation are larger as compared to when social influence is absent, when these indicators are provided to people before they form their own judgements about the news. We conclude by providing implications for better utilizing AI to fight misinformation.
Towards More Gender-Inclusive Q&As
Authors: Dubois Patrick Marcel Joseph , Maftouni Mahya , Bunt Andrea
Published: November 2022

Online Question and Answer communities (Q&As) are popular spaces for learning and sharing knowledge. However, prior research suggests that Q&As may not be appealing to and inclusive of men and women, with absent social considerations listed as a potential contributing factor. We investigate how additional community presence information can affect users' perceptions of and engagement with a Q&A for graphic design software. Through a 10-day task-based field study with 30 participants (14 women, 14 men, 2 non-binary), we uncover how community presence information can humanize the Q&A and play a role in promoting an inclusive environment. On the other hand, some participants question if community presence information belongs in a Q&A and describe some privacy implications. The women in our sample also talked about the importance of diverse community demographics, while we did not observe this sentiment expressed by the men. Our findings contribute an understanding of how users perceive the role of community presence information within a Q&A. We also discuss how this information might impact women's future participation and engagement.
When Does it Become Harassment?
Authors: Kim Haesoo , Kim HaeEun , Kim Juho , Jang Jeong-woo
Published: November 2022

Calling out, a phenomenon where people publicly broadcast their critiques of someone to a larger audience using, has become increasingly common on social media. However, there has been concerns that it could develop into harassment, deteriorating the quality of public discourse by over-punishing individuals for minor transgressions. To investigate this phenomenon, we interviewed 32 Twitter users who had been called out, had called out, or had witnessed a calling out on Twitter. We found that a key determining factor that distinguishes criticism from harassment was the callee's ability to respond to or engage with the criticism, and that different stakeholders hold different perspectives toward how online harassment is defined. We also discovered that the distinction between callers and callees was not absolute, and that there was high interchangeability of roles both within and across events. Through these findings, we discuss design implications for the platform in promoting healthy discourse while preventing toxic behavior on social media.
"I've talked without intending to": Self-disclosure and Reciprocity via Embodied Avatar
Authors: Ichino Junko , Ide Masahiro , Yokoyama Hitomi , Asano Hirotoshi , Miyachi Hideo , Okabe Daisuke
Published: November 2022

Considering the importance of self-disclosure in building relationships, it is vital to investigate how self-disclosure is affected via avatars in virtual environments, as they are likely to become increasingly popular. Previous work has shown that using avatars increases friendliness and honesty. However, issues such as how and what types of avatars affect self-disclosure and reciprocity have not been fully explored. We conducted a study with 108 participants (54 dyads) discussing a personal topic using one of three communication media: videoconferencing, avatars with avatar-self appearance similarity, or avatars without avatar-self appearance similarity. The results showed that self-disclosure is most encouraged via the avatars without similarity. Reciprocity was formed via both types of avatars but not videoconferencing. Interestingly, although the participants disclosed more about themselves via avatars than via videoconferencing, there was no difference in their subjective experiences. It means that avatar users can disclose more about themselves without being particularly aware that they are using avatars, which suggests the usefulness of avatars to understand people's candid thoughts and feelings. Finally, we discuss the design implications for applications requiring self-disclosure.
Stop the [Image] Steal
Authors: Matatov Hana , Naaman Mor , Amir Ofra
Published: November 2022

Images are powerful. Visual information can attract attention, improve persuasion, trigger stronger emotions, and is easy to share and spread. We examine the characteristics of the popular images shared on Twitter as part of "Stop the Steal'', the widespread misinformation campaign during the 2020 U.S. election. We analyze the spread of the forty most popular images shared on Twitter as part of this campaign. Using a coding process, we categorize and label the images according to their type, content, origin, and role, and perform a mixed-method analysis of these images' spread on Twitter. Our results show that popular images include both photographs and text rendered as image. Only very few of these popular images included alleged photographic evidence of fraud; and none of the popular photographs had been manipulated. Most images reached a significant portion of their total spread within several hours from their first appearance, and both popular- and less-popular accounts were involved in various stages of their spread.