bluuebunny/crossref_metadata_2025 huggingface dataset:
Designing the Conversational Agent: Asking Follow-up Questions for Information Elicitation
Authors: Hu Jiaxiong , Guo Jingya , Tang Ningjing , Ma Xiaojuan , Yao Yuan , Yang Changyuan , Xu Yingqing
Published: April 2024

Conversational Agents (CAs) can facilitate information elicitation in various scenarios, such as semi-structured interviews. Current CAs can ask predetermined questions but lack skills for asking follow-up questions. Thus, we designed three approaches for CAs to automatically ask follow-up questions, i.e., follow-ups on concepts, follow-ups on related concepts, and general follow-ups. To investigate their effects, we conducted a user study (N=26) in which a CA interviewer asked follow-up questions generated by algorithms and crafted by human wizards. Our results showed that the CA's follow-up questions were readable and effective in information elicitation. The follow-ups on concepts and related concepts achieved a lower drop rate and better relevance, while the general follow-ups elicited more informative responses. Further qualitative analysis of the human-CA interview data revealed algorithm drawbacks and identified follow-up question techniques used by the human wizards. We provided design implications for improving information elicitation of future CAs based on the results.
DesignQuizzer: A Community-Powered Conversational Agent for Learning Visual Design
Authors: Peng Zhenhui , Chen Qiaoyi , Shen Zhiyu , Ma Xiaojuan , Oulasvirta Antti
Published: April 2024

Online design communities, where members exchange free-form views on others' designs, offer a space for beginners to learn visual design. However, the content of these communities is often unorganized for learners, containing many redundancies and irrelevant comments. In this paper, we propose a computational approach for leveraging online design communities to run a conversational agent that assists informal learning of visual elements (e.g., color and space). Our method extracts critiques, suggestions, and rationales on visual elements from comments. We present DesignQuizzer, which asks questions about visual design in UI examples and provides structured comment summaries. Two user studies demonstrate the engagement and usefulness of DesignQuizzer compared with the baseline (reading reddit.com/r/UI_design). We also showcase how effectively novices can apply what they learn with DesignQuizzer in a design critique task and a visual design task. We discuss how to use our approach with other communities and offer design considerations for community-powered learning support tools.
Emotion Work in Caregiving: The Role of Technology to Support Informal Caregivers of Persons Living With Dementia
Authors: Smriti Diva , Wang Lu , Huh-Yoo Jina
Published: April 2024

The CSCW and HCI community has increasingly examined ways to support informal caregivers through technology, given the increasing burden and its consequences on caregivers' emotional and physical health. In this paper, we interviewed 12 informal caregivers of Persons Living With Dementia (PLWD) to understand their needs and current coping strategies for overcoming caregiving burden, specifically around emotion work. The caregivers associated different personal meanings with caregiving. Participants wanted technology to take over some of the utilitarian, mundane caregiving tasks. At the same time, they did not want technology to take over the tasks that fostered personal connections with PLWD. As the disease progressed, caregivers started to lose their perceived bond with PLWD, making it more challenging to juggle between rewarding, positive emotions with negative experiences. We discuss such complexity of emotion work using the notion of Invisible Work to understand when technology should or should not support the emotion work engaged in informal caregiving.
Empirically Understanding the Potential Impacts and Process of Social Influence in Human-AI Teams
Authors: Flathmann Christopher , Duan Wen , Mcneese Nathan J. , Hauptman Allyson , Zhang Rui
Published: April 2024

In the coming years, Artificial Intelligence (AI) will be applied as a teammate that works alongside and collaborates with humans. Prior research in teaming and CSCW has shown that teammates have the ability to change the thoughts and behaviors of each other through simple interactions in a process known as social influence. However, to date, research has yet to identify the social influence that AI teammates could have in these human-AI teams, which has led to a limited understanding of how AI teammates will change the behaviors of their human teammates. To remedy this gap, we conduct a mixed-methods study (N=33) with young individuals to explore how humans could behaviorally adapt and perceive their behavioral adaptation due to interaction with an AI teammate. Qualitative results report that perceived three unique stages they had to experience for the social influence of their AI teammate to lead to adaptation (i.e., perceiving a sense of control, identifying a technological or performative justification, and gaining first-hand experience). Quantitative results validate and illustrate the results of this perceived process, as results show that participants adapted their behaviors to complement the behaviors of different types of AI teammates. This study contributes to the CSCW/HCI field by developing an initial understanding of AI teammates' social influence in human-AI teams, which will be a pivotal design and research consideration in future efforts.
Examining the Social Aspects of Pregnancy Tracking Applications
Authors: Lu Xi , Powell Jacquelyn E. , Agapie Elena , Chen Yunan , Epstein Daniel A.
Published: April 2024

Pregnancy is a significant but stressful life transition, requiring effort from multiple stakeholders including expectant parents, family members, and friends to navigate. Existing work has primarily focused on understanding and supporting the technology use of pregnant people, neglecting other stakeholders' needs and participation. We therefore consider how pregnancy tracking apps both improve and interfere with the reconfiguration of social relationships caused by pregnancy, drawing on insights from family sociology to examine how these relationships evolve over pregnancy and the transition to parenthood. We reviewed the features of 20 pregnancy tracking apps, and analyzed 4,709 public reviews of them, finding that stakeholders used apps to bond with one another around the excitement of pregnancy, build a prenatal relationship with the fetus, and co-manage pregnancy-related logistical tasks. We find that not accounting for fetal demographics and users' identities, along with socio-cultural norms around gender and parenting roles, often inhibit these collaborative practices. We therefore suggest designing collaborative pregnancy tracking technology that considers both inclusiveness and specificity regarding stakeholders' different roles and relationships to pregnancy.
Exploring Effects of Chatbot's Interpretation and Self-disclosure on Mental Illness Stigma
Authors: Cui Yichao , Lee Yu-Jen , Jamieson Jack , Yamashita Naomi , Lee Yi-Chieh
Published: April 2024

Chatbots are increasingly being used in mental healthcare - e.g., for assessing mental-health conditions and providing digital counseling - and have been found to have considerable potential for facilitating people's behavioral changes. Nevertheless, little research has examined how specific chatbot designs may help reduce public stigmatization of mental illness. To help fill that gap, this study explores how stigmatizing attitudes toward mental illness may be affected by conversations with chatbots that have 1) varying ways of expressing their interpretations of participants' statements and 2) different styles of self-disclosure. More specifically, we implemented and tested four chatbot designs that varied in terms of whether they interpreted participants' comments as stigmatizing or non-stigmatizing, and whether they provided stigmatizing, non-stigmatizing, or no self-disclosure of chatbot's own views. Over the two-week period of the experiment, all four chatbots' conversations with our participants centered on seven mental-illness vignettes, all featuring the same character. We found that the chatbot featuring non-stigmatizing interpretations and non-stigmatizing self-disclosure performed best at reducing the participants' stigmatizing attitudes, while the one that provided stigmatizing interpretations and stigmatizing self-disclosures had the least beneficial effect. We also discovered side effects of chatbot's self-disclosure: notably, that chatbots were perceived to have inflexible and strong opinions, which undermined their credibility. As such, this paper contributes to knowledge about how chatbot designs shape users' perceptions of the chatbots themselves, and how chatbots' interpretation and self-disclosure may be leveraged to help reduce mental-illness stigma.
"Fact-checks are for the Top 0.1%": Examining Reach, Awareness, and Relevance of Fact-Checking in Rural India
Authors: Seelam Ananya , Paul Choudhury Arnab , Liu Connie , Goay Miyuki , Bali Kalika , Vashistha Aditya
Published: April 2024

Social media platforms have witnessed an unprecedented growth in users from rural communities in India. Many of these users are new to online information environments and are highly susceptible to misinformation. Fact-checking has the potential to reduce the proliferation and impact of misinformation; however, little is known about how fact-checking organizations in India serve rural users. To fill this gap, we conducted interviews with 12 prominent fact-checking organizations in India to understand their current practices and challenges in providing their services to rural users and the associated human and technological infrastructure they use. We discovered several measures that fact-checking organizations take to increase the reach, awareness, and relevance of fact-checked content for rural users, such as engaging with stringer networks and utilizing vernacular languages. However, fact-checking organizations also face severe challenges that limit both the scale of their work and engagement from rural users. Drawing on these findings, we provide design and policy recommendations to improve the reach, awareness, and relevance of fact-checked content for social media users in rural areas.
Foundations for Enabling People to Recognise Misinformation in Social Media News based on Retracted Science
Authors: Yaqub Waheeb , Kay Judy , Goldwater Micah
Published: April 2024

For many people, social media is an important way to consume news on important topics like health. Unfortunately, some influential health news is misinformation because it is based on retracted scientific work. Ours is the first work to explore how people can understand this form of misinformation and how an augmented social media interface can enable them to make use of information about retraction. We report a between-subjects think-aloud study with 44 participants, where the experimental group used our augmented interface. Our results indicate that this helped them consider retraction when judging the credibility of news. Our key contributions are foundational insights for tackling the problem, revealing the interplay between people's understanding of scientific retraction, their prior beliefs about a topic and the way they use a social media interface that provides access to retraction information.
Governance Capture in a Self-Governing Community: A Qualitative Comparison of the Croatian, Serbian, Bosnian, and Serbo-Croatian Wikipedias
Authors: Kharazian Zarine , Starbird Kate , Hill Benjamin Mako
Published: April 2024

What types of governance arrangements make some self-governed online groups more vulnerable to disinformation campaigns? We present a qualitative comparative analysis of the Croatian and Serbian Wikipedia editions to answer this question. We do so because between at least 2011 and 2020, the Croatian language version of Wikipedia was taken over by a small group of administrators who introduced far-right bias and outright disinformation. Dissenting editorial voices were reverted, banned, and blocked. Although Serbian, Bosnian, and Serbo-Croatian Wikipedias share many linguistic and cultural features, and faced similar threats, they seem to have largely avoided this fate. Based on a grounded theory analysis of interviews with members of these communities and others in cross-functional platform-level roles, we propose that the convergence of three features---high perceived value as a target, limited early bureaucratic openness, and a preference for personalistic, informal forms of organization over formal ones---produced a window of opportunity for governance capture on Croatian Wikipedia. Our findings illustrate that online community governing infrastructures can play a crucial role in systematic disinformation campaigns and other influence operations.
How Personal Value Orientations Influence Behaviors in Digital Citizen Science
Authors: Jeong Eunmi (Ellie) , Jackson Corey , Dowthwaite Liz , Johnson Cliff , Trouille Laura
Published: April 2024

While much research has examined motivations for contributing to citizen science projects, few studies have considered the role of personal values in directing citizen scientists' interactions and contribution patterns. We investigated whether personal values systematically influence the behaviors of individuals who use the Zooniverse platform to select and contribute to citizen science projects. In this paper, we present the results of a research study where we launched a large-scale survey (N = 2,605) to capture personal values using Schwartz's Portrait Values Questionnaire (PVQ-21). We also extracted system log data from participant interactions on Zooniverse. Our results align with previous research suggesting intrinsic type motivators and values tend to drive specific modes of interaction, e.g., exploring projects in different disciplines. We also see that interaction in social spaces, e.g., discussion boards, is driven by values with a personal focus (e.g., self-enhancement) and social focus. Given these results, we provide several suggestions for managing these and similar projects.
"I'm Constantly in This Dilemma": How Migrant Technology Professionals Perceive Social Media Recommendation Algorithms
Authors: Pyle Cassidy , Zhang Ben Zefeng , Haimson Oliver L. , Andalibi Nazanin
Published: April 2024

Migrants experience unique needs and use social media, in part, to address them. While prior work has primarily focused on migrant populations who are vulnerable socio-economically and legally, less is known about how highly educated migrant populations use social media. Additionally, a growing body of work focuses on algorithmic perceptions and resistance, primarily from laypersons' perspectives rather than people with high degrees of algorithmic literacy. To address these gaps, we draw from interviews with 20 Chinese-born migrant technology professionals. We found that social media played an integral role in helping participants meet their unique needs but that participants perceived social media algorithms to negatively shape the content they consumed, which ultimately influenced their mobility-related aspirations and goals. We discuss how findings challenge the promise of algorithmic literacy and contribute to a human-centered conceptualization of algorithmic mobility as socially and algorithmically produced motion that concerns the movement of physical bodies and interactions as well as associated digital movement. Specifically, we introduce a fourth dimension of algorithmic mobility: algorithmically curated content on social media and elsewhere based on facets of users' identities directly influences users' mobility-related aspirations and goals, such as how, when, and where they go. Finally, we call for transnational policy interventions related to algorithms and highlight design considerations around content moderation, algorithmic user-control, and contestability.
"I Felt Everyone Was a Streamer": An Empirical Study on What Makes Avatar Collective Streaming Engaging
Authors: Chen Qijia , Gan Jingwen , Bellucci Andrea , Jacucci Giulio
Published: April 2024

A novel participatory livestreaming genre, Avatar Collective Streaming, is gaining traction. Beyond traditional audience participation mechanisms, such as chat messages or commands, these livestreams allow viewers to join, socially interact, and participate through avatars in a software-driven virtual scenario without requiring the presence of a human streamer. From observations of livestreaming sessions and interviews with regular users (n=23), we define the main features of this novel form of livestreaming and we analyze what makes it engaging for participants, as well as factors that limit the user experience. The use of avatars affords a strong sense of presence and participation, and together with the absence of a streamer, it shapes new forms of sociability, being together, and belonging. Challenges include repetitive content and overcrowding. We provide design implications for synchronous collective participation scenarios and opportunities for software-driven content generation.
I Just Don't Quite Fit In: How People of Colour Participate in Online and Offline Climate Activism
Authors: Wong Priscilla N. Y. , Singh Aneesha , Brumby Duncan P.
Published: April 2024

Participation in climate activism is often facilitated by joining groups on digital platforms, for online and in-person participation in the movement. However, despite the easy access to communities digitally, people of colour (POC) are underrepresented in the UK in climate activism. Little research provides insight into why the voices of POC are underrepresented and how to level the playing field for participation in climate activism, which is just as important to POC. To investigate this, we conducted a qualitative semi-structured interview study with POC who are active in the climate movement (N=12). We identified five main themes: (i) gaining membership to the climate activism community, (ii) experiencing challenges in belonging with respect to identity characteristics, (iii) participating in protest through relevant issues and values, (iv) feeling fear due to differences and marginalisation, and (v) developing strategies for control and utilising anonymity. Our findings show how people's racial and other minoritised identity is crucial in influencing their sense of belonging and community and in turn their participation in climate activism and perhaps other opinion-based movements. For movements to be more inclusive, we urge the HCI and CSCW community to rethink designs influenced by structures of power and centre diverse values and issues instead of universal ones to amplify the voices of minoritised identities. Suggestions on how technologies could achieve this are discussed.
"If it is easy to understand then it will have value": Examining Perceptions of Explainable AI with Community Health Workers in Rural India
Authors: Okolo Chinasa T. , Agarwal Dhruv , Dell Nicola , Vashistha Aditya
Published: April 2024

AI-driven tools are increasingly deployed to support low-skilled community health workers (CHWs) in hard-to-reach communities in the Global South. This paper examines how CHWs in rural India engage with and perceive AI explanations and how we might design explainable AI (XAI) interfaces that are more understandable to them. We conducted semi-structured interviews with CHWs who interacted with a design probe to predict neonatal jaundice in which AI recommendations are accompanied by explanations. We (1) identify how CHWs interpreted AI predictions and the associated explanations, (2) unpack the benefits and pitfalls they perceived of the explanations, and (3) detail how different design elements of the explanations impacted their AI understanding. Our findings demonstrate that while CHWs struggled to understand the AI explanations, they nevertheless expressed a strong preference for the explanations to be integrated into AI-driven tools and perceived several benefits of the explanations, such as helping CHWs learn new skills and improved patient trust in AI tools and in CHWs. We conclude by discussing what elements of AI need to be made explainable to novice AI users like CHWs and outline concrete design recommendations to improve the utility of XAI for novice AI users in non-Western contexts.
Images Connect Us Together: Navigating a COVID-19 Local Outbreak in China Through Social Media Images
Authors: He Changyang , He Lu , Yang Wenjie , Li Bo
Published: April 2024

Social media images, curated or casual, have become a crucial component of communicating situational information and emotions during health crises. Despite its prevalence and significance in informational dissemination and emotional connection, there lacks a comprehensive understanding of visual crisis communication in the aftermath of a pandemic which is characterized by uncertain local situations and emotional fatigue. To fill this gap, this work collected 345,423 crisis-related posts and 65,376 original images during the Xi'an COVID-19 local outbreak in China, and adopted a mixed-methods approach to understanding themes, goals, and strategies of crisis imagery. Image clustering captured the diversity of visual themes during the outbreak, such as text images embedding authoritative guidelines and "visual diaries" recording and sharing the quarantine life. Through text classification of the post that visuals were situated in, we found that different visual themes highly correlated with the informational and emotional goals of the post text, such as adopting text images to convey the latest policies and sharing food images to express anxiety. We further unpacked nuanced strategies of crisis image use through inductive coding, such as signifying authority and triggering empathy. We discuss the opportunities and challenges of crisis imagery and provide design implications to facilitate effective visual crisis communication.
Improving Work-Nonwork Balance with Data-Driven Implementation Intention and Mental Contrasting
Authors: Sefidgar Yasaman S. , Jörke Matthew , Suh Jina , Saha Koustuv , Iqbal Shamsi , Ramos Gonzalo , Czerwinski Mary
Published: April 2024

Work-nonwork balance is an important aspect of workplace well-being with associations to improved physical and mental health, job performance, and quality of life. However, realizing work-nonwork balance goals is challenging due to competing demands and limited resources within organizational and interpersonal contexts. These challenges are compounded by technologies that blur the boundaries of work and nonwork in the always-on work cultures. At an individual level, such challenges can be subsided through the effective application of self-regulation techniques, such as implementation intentions and mental contrasting (IIMC). Further supporting these techniques through reflection on personal data, we implement the idea of data-driven IIMC into a self-tracking and behavior planning system and evaluate it in a three-week between-participant study with 43 information workers who used our system for improving work-nonwork balance. We find evidence that reflection on personal data improves awareness of behavior plan compliance and rescheduling, which are important in realizing work-nonwork balance goals. We also observe the value of micro-reflection, reflection on limited data of the very recent past, for IIMC. Our findings highlight opportunities for automation in data collection and sense-making and for further exploring the role of data-driven IIMC as boundary negotiating artifacts in support of work-nonwork balance goals.
Infrastructuring Community Fridges for Food Commoning
Authors: Jo Jeongwon , Xie Jingyi , Aiyer Priyanka , Knearem Tiffany , Carroll John M.
Published: April 2024

Beginning in 2020, the COVID-19 pandemic and its economic repercussions exacerbated food insecurity in the United States. Government-led infrastructure was depleted as a result of a dramatic increase in the number of individuals requesting basic necessities and food aid, and grassroots attempts to alleviate the resource shortage increased. The Community Fridge movement was one of these initiatives that combated food insecurity and food waste. It consisted of local community members sharing surplus food with neighbors via a shared refrigerator placed on a sidewalk. We conducted semi-structured interviews with its 17 users to understand how they practice information, human, and social infrastructuring work, as well as how their core values shaped norms for managing refrigerators and surplus food as the commons in local communities. We discuss how the concepts of commoning and infrastructuring may complement one another, which can help design value-embedded interventions to promote infrastructuring practices that build resilience and sustain commoning practices.
"It's hard for him to make choices sometimes and he needs guidance": Re-orienting Parental Control for Children
Authors: Dumaru Prakriti , Atashpanjeh Hanieh , Al-Ameen Mahdi Nasrullah
Published: April 2024

With access to devices and online platforms at an increasingly younger age, it is essential to protect children from potential online risks. In our studies, we particularly focused the parents who have a child under 13 years of age. To this end, deriving from developmental psychology, we base our low-fidelity prototype design (termed as 'treatment') on a set of design principles focusing on open communication, instilling self-regulation, and availing granularity along with designs of existing Google's parental control as a baseline. First, we conducted semi-structured interviews with 21 parents to understand their perceptions, including suggestions for design improvement within our prototype. Then, we conducted an online study over MTurk with 156 participants to compare and evaluate the treatment condition against the baseline in the realm of our design principles. As reflected in our results, parents appreciated the insights into the children's activities to have a meaningful discussion with them, the significance of nudges in instilling self-regulation, and the usefulness of granularity in a wide range of contexts, including shielding the children from inappropriate content and defining purpose-specific device usage. The findings from our studies lead to the recommendations, and the guideline for future research in the sphere of developmental parenting and inclusiveness.
"It's the most fair thing to do but it doesn't make any sense": Perceptions of Mathematical Fairness Notions by Hiring Professionals
Authors: Sarkar Priya , Liem Cynthia C. S.
Published: April 2024

We explore the alignment of organizational representatives involved in hiring processes with five different, commonly proposed fairness notions. In a qualitative study with 17 organizational professionals, for each notion, we investigate their perception of understandability, fairness, potential to increase diversity, and practical applicability in the context of early candidate selection in hiring. In this, we do not explicitly frame our questions as questions of algorithmic fairness, but rather relate them to current human hiring practice. As our findings show, while many notions are well understood, fairness, potential to increase diversity and practical applicability are rated differently, illustrating the importance of understanding the application domain and its nuances, and calling for more interdisciplinary and human-centered research into the perception of mathematical fairness notions.
It Takes Two to Negotiate: Modeling Social Exchange in Online Multiplayer Games
Authors: Jaidka Kokil , Ahuja Hansin , Ng Lynnette Hui Xian
Published: April 2024

Online games are dynamic environments where players interact with each other, which offers a rich setting for understanding how players negotiate their way through the game to an ultimate victory. This work studies online player interactions during the turn-based strategy game, Diplomacy. We annotated a dataset of over 10,000 chat messages for different negotiation strategies and empirically examined their importance in predicting long- and short-term game outcomes. Although negotiation strategies can be predicted reasonably accurately through the linguistic modeling of the chat messages, more is needed for predicting short-term outcomes such as trustworthiness. On the other hand, they are essential in graph-aware reinforcement learning approaches to predict long-term outcomes, such as a player's success, based on their prior negotiation history. We close with a discussion of the implications and impact of our work.
Leveraging Large Language Models to Power Chatbots for Collecting User Self-Reported Data
Authors: Wei Jing , Kim Sungdong , Jung Hyunhoon , Kim Young-Ho
Published: April 2024

Large language models (LLMs) provide a new way to build chatbots by accepting natural language prompts. Yet, it is unclear how to design prompts to power chatbots to carry on naturalistic conversations while pursuing a given goal such as collecting self-report data from users. We explore what design factors of prompts can help steer chatbots to talk naturally and collect data reliably. To this aim, we formulated four prompt designs with different structures and personas. Through an online study (N = 48) where participants conversed with chatbots driven by different designs of prompts, we assessed how prompt designs and conversation topics affected the conversation flows and users' perceptions of chatbots. Our chatbots covered 79% of the desired information slots during conversations, and the designs of prompts and topics significantly influenced the conversation flows and the data collection performance. We discuss the opportunities and challenges of building chatbots with LLMs.
Linguistically Differentiating Acts and Recalls of Racial Microaggressions on Social Media
Authors: Gunturi Uma Sushmitha , Kumar Anisha , Ding Xiaohan , Rho Eugenia H.
Published: April 2024

In this work, we examine the linguistic signature of online racial microaggressions (acts) and how it differs from that of personal narratives recalling experiences of such aggressions (recalls) by Black social media users. We manually curate and annotate a corpus of acts and recalls fromin-the-wild social media discussions, and verify labels with Black workshop participants. We leverage Natural Language Processing (NLP) and qualitative analysis on this data to classify (RQ1), interpret (RQ2), and characterize (RQ3) the language underlying acts and recalls of racial microaggressions in the context of racism in the U.S. Our findings show that neural language models (LMs) can classify acts and recalls with high accuracy (RQ1) with contextual words revealing themes that associate Blacks with objects that reify negative stereotypes (RQ2). Furthermore, overlapping linguistic signatures between acts and recalls serve functionally different purposes (RQ3), providing broader implications to the current challenges in content moderation systems on social media.
Mapping the Landscape of Independent Food Delivery Platforms in the United States
Authors: Liu Yuhan , Liaqat Amna , Zhang Xingjian , Espinosa Mariana Consuelo Fernández , Manjunatha Ankhitha , Yang Alexander , Papakyriakopoulos Orestis , Monroy-Hernández Andrés
Published: April 2024

Beyond the well-known giants like Uber Eats and DoorDash, there are hundreds of independent food delivery platforms in the United States. However, little is known about the sociotechnical landscape of these "indie'' platforms. In this paper, we analyzed these platforms to understand why they were created, how they operate, and what technologies they use. We collected data on 495 indie platforms and detailed survey responses from 29 platforms. We found that personalized, timely service is a central value of indie platforms, as is a sense of responsibility to the local community they serve. Indie platforms are motivated to provide fair rates for restaurants and couriers. These alternative business practices differentiate them from mainstream platforms. Though indie platforms have plans to expand, a lack of customizability in off-the-shelf software prevents independent platforms from personalizing services for their local communities. We show that these platforms are a widespread and longstanding fixture of the food delivery market. We illustrate the diversity of motivations and values to explain why a one-size-fits-all support is insufficient, and we discuss the siloing of technology that inhibits platforms' growth. Through these insights, we aim to promote future HCI research into the potential development of public-interest technologies for local food delivery.
Navigating the Job-Seeking Journey: Challenges and Opportunities for Digital Employment Support in Kashmir
Authors: Wani Asra Sakeen , Joshi Ishika , Singh Pushpendra
Published: April 2024

The issue of youth unemployment is a global concern, with active initiatives, policies, and technologies in place to support employment seekers. Despite these efforts, youth unemployment in various regions is attributed to the complex challenges that impede access to resources, particularly in contexts characterized by socio-political unrest. To understand the use of job-seeking resources in such a context, we situate our work in the region of Jammu & Kashmir, which has a long-standing history of socio-political conflict ongoing for more than three decades. For this work, we conducted 21 semi-structured interviews with participants from Kashmir to understand their current job-seeking practices and the challenges they encounter during the entire process. Our findings present the systemic infrastructural challenges the youths face due to the ongoing crisis. Analyzing the youths' workarounds to mitigate these challenges, we discuss how we might leverage these workarounds into designing systems while navigating through the contextual complexities. We discuss the challenges of designing in the context and provide design recommendations to support job seekers.
Opportunities and Challenges in Using Tangible, Teleoperated Voice Agents in Kid-Driven Moments in Play Among Families with Neurodivergent Children
Authors: Currin Flannery Hope , Kilcoin Cassidy , Peterman Kerry , Rector Kyle , Hourcade Juan Pablo
Published: April 2024

Child-agent interaction research has largely focused on automated voice agents, although privacy concerns and quality of interactions serve as a rationale for using teleoperated agents in some settings. Research on neurodivergent children's interactions with voice agents has largely focused on therapy and classroom contexts as opposed to home contexts. We conducted a remote case study via Zoom observing six families with neurodivergent children playing with a tangible, parent-operated voice agent at home for up to eight weeks. We used quantitative measures of agent utilization, qualitative analysis of video recordings, and parent survey responses to identify implications for teleoperation interface design for playful voice agents. Based on our analysis, we argue joint media engagement principles are applicable to a broader set of play activities, and teleoperated agents present affordances and challenges distinct from those of automated agents.
OSINT Research Studios: A Flexible Crowdsourcing Framework to Scale Up Open Source Intelligence Investigations
Authors: Mukhopadhyay Anirban , Venkatagiri Sukrit , Luther Kurt
Published: April 2024

Open Source Intelligence (OSINT) investigations, which rely entirely on publicly available data such as social media, play an increasingly important role in solving crimes and holding governments accountable. The growing volume of data and complex nature of tasks, however, means there is a pressing need to scale and speed up OSINT investigations. Expert-led crowdsourcing approaches show promise, but tend to either focus on narrow tasks or domains, or require resource-intense, long-term relationships between expert investigators and crowds. We address this gap by providing a flexible framework that enables investigators across domains to enlist crowdsourced support for discovery and verification of OSINT. We use a design-based research (DBR) approach to develop OSINT Research Studios (ORS), a sociotechnical system in which novice crowds are trained to support professional investigators with complex OSINT investigations. Through our qualitative evaluation, we found that ORS facilitates ethical and effective OSINT investigations across multiple domains. We also discuss broader implications of expert-crowd collaboration and opportunities for future work.
Privacy Norms of Transformative Fandom: A Case Study of an Activity-Defined Community
Authors: Marsh Abby , Lerner Ada
Published: April 2024

Transformative media fandom is a remarkably coherent, long-lived, and diverse community united primarily by shared engagement in the varied activities of fandom. Its social norms are highly-developed and frequently debated, and have been studied by the CSCW and Media Studies communities in the past, but rarely using the tools and theories of privacy, despite fannish norms often bearing strongly on privacy. We use privacy scholarship and existing theories thereof to examine these norms and bring an additional perspective to understanding fandom communities. In this work, we analyze over 250,000 words of "meta'' essays and comments on those essays, reflecting the views and debates of hundreds of fans on these privacy norms. Drawing on Solove's theory of privacy as an aggregation of different ideas and on a variety of other academic theories of privacy, we analyze these norms as highly effective at protecting the integrity of fannish activities. We then articulate the value of studying these sorts of diverse "activity-defined'' communities, arguing that such approaches grant us greater power to understand privacy experiences in ways that are specific, contextual, and intersectional yet still generalizable where possible.
Redistrict: Online Public Deliberation Support that Connects and Rebuilds Inclusive Communities
Authors: Sistrunk Andreea , Self Nathan , Biswas Subhodip , Luther Kurt , Verdezoto Nervo , Ramakrishnan Naren
Published: April 2024

Public deliberations are often a staple ingredient in community decision-making. However, traditional, time-constrained, in-person debates can become highly polarized, eroding trust in authorities, and leaving the community divided. This is the case in redistricting deliberations for public school zoning. Seeking alternative ways of support, we evaluated the potential introduction of an online platform that combines multiple streams of data, visualizes school attendance boundaries, and enables the manipulation of representations of land parcels. To capture multiple stakeholders' values about the potential to enhance public engagement in school rezoning decision-making through an online platform, we conducted interviews with 12 participants with previous experiences in traditional, in-person deliberations. Insights from the interviews highlight the several roles an online platform could take, especially as it provides alternative means of participation (online, synchronous, and asynchronous). Additionally, we discuss the potential for technology to increase the visibility and participation of multiple community actors in public deliberations and present implications for the design of future tools to support public decision-making.
ReSPect: Enabling Active and Scalable Responses to Networked Online Harassment
Authors: Kim Haesoo , Lee Juhoon , Jang Jeong-Woo , Kim Juho
Published: April 2024

Online harassment, especially networked harassment at scale, has become an increasingly serious issue that pervades many social media platforms. In this study, we investigated the nature and harms of networked harassment on Twitter through design workshops (n = 11) and developed a set of design goals focusing on empowering the individual to fight back against harassment. We designed Re:SPect, an anti-harassment tool promoting scalable and active responses to networked harassment. We evaluated Re:SPect through a simulated scenario-based study with Twitter users (n = 18) who had directly or indirectly experienced networked harassment. Our findings reveal that users felt safer and more empowered as Re:SPect enabled them to manage interactions with a larger audience. Users felt less anxious about the potential of being harassed, while the summarization features of Re:SPect allowed users to perceive the situation more objectively. Based on the findings, we discuss how Re:SPect's features could be utilized in promoting healthier online discussion, as well as theoretical implications in designing such systems.
Smart "Error"! Exploring Imperfect AI to Support Creative Ideation
Authors: Liu Fang , Lv Junyan , Cui Shenglan , Luan Zhilong , Wu Kui , Zhou Tongqing
Published: April 2024

Designers widely accept AI as a partner in the design process for its efficient and intelligent decision-making. However, AI is often not perfect, and AI error often makes humans dumbfounded. Literature has pointed out the value of such AI error, while still leaving its inspiration essence and application strategies uncharted from the practice perspective. This work focuses on bridging the practice gap by looking into and exploiting the imaginative "mislabeled" objects of object detection models. To gain insights into the inspiration of AI "error", we collected a dedicated AI "error" dataset from object detection and invited eight designers to share divergent comments on the "mislabeled" objects. Coding was then performed on the comments, which summarizes the inspiration of AI "error" into six atomic dimensions. Subsequently, we took a step further to an exploratory study, a comparative ideation experiment with 20 designers, investigating how to apply these inspiration dimensions to create ideas. Questionnaire and interview results revealed that essential inspiration of AI "error" could positively activate creativity, especially the "Outline" dimension. A design model CETR is then formulated by summarizing the application of atomic inspiration of "error" into four forms of creativity, which could be taken as a guideline for cooperative design with AI "error". In addition, we also sketch two approaches to generate more inspiring and applicable AI "error", elaborate on two principal characteristics of AI "error" for promoting creativity, and propose three strategies for better co-creating with AI "error". Finally, we provide insight into design research about AI self-awareness and human-AI collaboration.
The Soul of Work: Evaluation of Job Meaningfulness and Accountability in Human-AI Collaboration
Authors: Sadeghian Shadan , Uhde Alarith , Hassenzahl Marc
Published: April 2024

Work is an important part of our lives - not only as a way to earn a living but as a crucial source for experiencing meaningfulness. The introduction of autonomous systems (or in the widest sense "artificial intelligence", AI) will fundamentally impact work practices. However, while most existing models of human-AI collaboration focus on performance goals, less is known about their potential influence on job satisfaction. In this paper, we present an online experiment in which we compared the perception of job meaningfulness and accountability in a human-AI collaboration across three interaction paradigms: Supervisory, Advisory, and Interactive. Our results showed that, unlike the common notion of supervisory control, people find their job more satisfying when they directly interact with the AI and are involved and remain accountable for action and decision-making. Introducing AI as a teammate in the interactive paradigm was associated with the highest job meaningfulness.
Towards Enforcing Good Digital Citizenship: Identifying Opportunities for Adolescent Online Safety Nudges
Authors: Obajemu Oluwatomisin , Agha Zainab , Chowdhury Farzana A. , Wisniewski Pamela J.
Published: April 2024

With the prevalence of risks encountered by youth online, strength-based approaches such as nudges have been recommended as potential solutions to guide teens toward safer decisions. However, most nudging interventions to date have not been designed to cater to teens' unique needs and online safety concerns. To address this gap, this study provided a comprehensive view of adolescents' feedback on online safety nudges to inform the design of more effective online safety interventions. We conducted 12 semi-structured interviews and 3 focus group sessions with 21 teens (13 - 17 years old) via Zoom to get their feedback on three types of nudge designs from two opposing perspectives (i.e., risk victim and perpetrator) and for two different online risks (i.e., Information Breaches and Cyberbullying). Based on the teens' responses, they expressed a desire that nudges need to move beyond solely warning the user to providing a clear and effective action to take in response to the risk. They also identified key differences that affect the perception of nudges in effectively addressing an online risk, they include age, risk medium, risk awareness, and perceived risk severity. Finally, the teens identified several challenges with nudges such as them being easy to ignore, disruptive, untimely, and possibly escalating the risk. To address these, teens recommended clearer and contextualized warnings, risk prevention, and nudge personalization as solutions to ensure effective nudging. Overall, we recommend online safety nudges be designed for victim guidance while providing autonomy to control their experiences, and to ensure accountability and prevention of risk perpetrators to restrict them from causing harm.
Towards Inclusive Futures for Worker Wellbeing
Authors: Pendse Sachin R. , Massachi Talie , Mahdavimoghaddam Jalehsadat , Butler Jenna , Suh Jina , Czerwinski Mary
Published: April 2024

The global COVID-19 pandemic has spurred on new collaborations across borders, and emphasized the importance of supporting wellbeing in the workplace, whether that workplace is hybrid, remote, or in-person. Work in CSCW, HCI, and organizational psychology has explored how people come to understand their wellbeing at work, and the role of identity, culture, and organizational factors in that process. In this study, we build on this past research and explore the importance of these factors when designing tools that support worker wellbeing for location-independent teams. We ask the question: how did organizational, cultural, and individual factors influence how workers understood their workplace wellbeing needs during the move to remote work? To investigate this question, we conduct a large scale linguistic analysis of 13,265 diary entries collected between 2020 - 2022, and complement it with in-depth interviews with 26 global employees, exploring intersections between technology, context, and wellbeing needs. We utilize this data to analyze the broader human infrastructure supporting hybrid and remote work, demonstrating how ideas around wellbeing are influenced by the (often technology-mediated) environment around both information and essential workers, and power differentials within it. Building on our findings, we provide recommendations for how technology design can better support more diverse and inclusive forms of worker wellbeing.