bluuebunny/crossref_metadata_2025 huggingface dataset:
Chilling Tales: Understanding the Impact of Copyright Takedowns on Transformative Content Creators
Authors: Fiesler Casey , Paup Joshua , Zacher Corian
Published: October 2023

Though current conversations around automated content moderation often focus on newer contexts for this technology such as harassment or misinformation, one other important use case is copyright detection systems such as YouTube's Content ID. This context for content removals online has some unique properties such as its relationship to legal requirements (Section 512 of the Digital Millennium Copyright Act that governs copyright notice-and-takedown), and provides a longstanding example of the intersection between policy, online platform design, and algorithms. Based on qualitative analysis of survey data, this paper examines the impact of DMCA takedowns and automated copyright-related content removals on a community of content creators who primarily share transformative works, remixed content that makes use of copyrighted material. Our data reveals patterns of chilling effects related to prior experiences and perceptions of policies and process. Based on these findings we make recommendations for platform policy and design, education, and advocacy, and discuss the implications of our findings for current and proposed laws.
People Perceive Algorithmic Assessments as Less Fair and Trustworthy Than Identical Human Assessments
Authors: Mok Lillio , Nanda Sasha , Anderson Ashton
Published: October 2023

Algorithmic risk assessments are being deployed in an increasingly broad spectrum of domains including banking, medicine, and law enforcement. However, there is widespread concern about their fairness and trustworthiness, and people are also known to display algorithm aversion, preferring human assessments even when they are quantitatively worse. Thus, how does the framing of who made an assessment affect how people perceive its fairness? We investigate whether individual algorithmic assessments are perceived to be more or less accurate, fair, and interpretable than identical human assessments, and explore how these perceptions change when assessments are obviously biased against a subgroup. To this end, we conducted an online experiment that manipulated how biased risk assessments are in a loan repayment task, and reported the assessments as being made either by a statistical model or a human analyst. We find that predictions made by the model are consistently perceived as less fair and less interpretable than those made by the analyst despite being identical. Furthermore, biased predictive errors were more likely to widen this perception gap, with the algorithm being judged even more harshly for making a biased mistake. Our results illustrate that who makes risk assessments can influence perceptions of how acceptable those assessments are - even if they are identically accurate and identically biased against subgroups. Additional work is needed to determine whether and how decision aids should be presented to stakeholders so that the inherent fairness and interpretability of their recommendations, rather than their framing, determines how they are perceived.
Understanding and Designing Multi-level Preventive Medication Support Against HIV for Men who Have Sex with Men in Taiwan
Authors: Yuan Chien Wen (Tina) , Tseng Yuan-Chi , Strong Carol
Published: October 2023

Sexual health is an important domain that deserves more HCI attention, such as supporting the practices of men who have sex with men (MSM) against HIV risks. One current clinical approach to addressing this issue is to use preventive medicine like pre-exposure prophylaxis (PrEP). As medication adherence of PrEP is challenging that involves users' individual knowledge, sex practices, relational status, and community support, technological mediation benefits from a human-centered perspective that goes beyond individual-level support to understand MSM's needs so as to design a holistic technological intervention for them. With an in-depth interview (n = 22) with MSM from two major cities in Taiwan, we drew on the theoretical framework of the social ecological model and identified three levels of influences, including individual, interpersonal, and sociocultural, that shape the enablers, inhibitors, risks and challenges, and support towards MSM's PrEP use. We proposed correspondent technological design implications to support what we found based on the understanding of our participants.
Ignore the Affordances; It's the Social Norms: How Millennials and Gen-Z Think About Where to Make a Post on Social Media
Authors: Taber Lee , Dominguez Sonia , Whittaker Steve
Published: October 2023

How do Millennial and Gen-Z young adults decide between competing social media when choosing where to post? Previous research argues that decisions can be modeled based on these users' Goals, and the Affordances, Features1, and Social Norms of those media. To evaluate this model, 19 participants were given different self-presentation scenarios and asked to choose between Twitter, Snapchat, Instagram, and TikTok. Participants also constructed a flowchart to represent their mental model of factors influencing their choices. Data suggest revisions to the model; rather than reflecting Affordances and Features, we found that Social Norms and Goals primarily drove participants' choices. Participants choose media based on a direct match between Goals and existing Social Norms. Only when they failed to detect such a match did participants consider Affordances and Features. We present a revised conceptual model based on these results and discuss social media design and theory implications.
Understanding the Benefits and Design of Chatbots to Meet the Healthcare Needs of Migrant Workers
Authors: Tseng Yuan-Chi , Jarupreechachan Weerachaya , Lee Tuan-He
Published: October 2023

Economically disadvantaged migrant workers are one of the most vulnerable groups in healthcare. Studies have shown that chatbots can help patients and health professionals in healthcare settings. However, the design of health chatbots for migrant workers has not been thoroughly investigated. Scenario-based interviews with nineteen participants, including ten economically disadvantaged Thai migrant workers and nine relevant stakeholders, were conducted to examine how they seek healthcare, obtain health information, and communicate with health professionals to gain a deeper understanding of the barriers that migrant workers encounter in healthcare. The findings of the interview show that migrant workers face a variety of barriers, such as a lack of familiarity with the healthcare system in the host country, language barriers, cultural barriers to seeking healthcare, and communication barriers with health professionals. Then, the technological design strategies and the benefits of health chatbots from the perspective of migrant workers were discussed, including their potential to help migrant workers navigate the healthcare system step-by-step, obtain reliable health information, improve their health literacy, and facilitate communication with health professionals. Finally, five design implications for chatbots were proposed to guide future development of health chatbots to help migrant workers. Policymakers and health professionals can benefit from the design implications of migrant worker-centered health chatbots when they develop health chatbots that promote the health and well-being of migrant workers.
The Shapes of the Fourth Estate During the Pandemic: Profiling COVID-19 News Consumption in Eight Countries
Authors: Yang Cai , Xie Lexing , Wu Siqi
Published: October 2023

News media is often referred to as the Fourth Estate, a recognition of its political power. New understandings of how media shape political beliefs and influence collective behaviors are urgently needed in an era when public opinion polls do not necessarily reflect election results and users influence each other in real-time under algorithm-mediated content personalization. In this work, we measure not only the average but also the distribution of audience political leanings for different media across different countries. The methodological components of these new measurements include a high-fidelity COVID-19 tweet dataset; high-precision user geolocation extraction; and user political leaning estimated from the within-country retweet networks involving local politicians. We focus on geolocated users from eight countries, profile user leaning distribution for each country, and analyze bridging users who have interactions across multiple countries. Except for France and Turkey, we observe consistent bi-modal user leaning distributions in the other six countries, and find that cross-country retweeting behaviors do not oscillate across the partisan divide. More importantly, this study contributes a new set of media bias estimates by averaging the leaning scores of users who share the URLs from media domains. Through two validations, we find that the new average audience leaning scores strongly correlate with existing media bias scores. Lastly, we profile the COVID-19 news consumption by examining the audience leaning distribution for top media in each country, and for selected media across all countries. Those analyses help answer questions such as: Does center media Reuters have a more balanced audience base than partisan media CNN and Fox News in the US? Does far-right media Breitbart attract any left-leaning readers in any countries? Does CNN reach a more balanced audience base in the US than in UK and Spain? In sum, our data-driven methods allow us to study media that are not often collected in editor-curated media bias reporting, especially in non-English-speaking countries. We hope that such cross-country research would inform media outlets of their effectiveness and audience bases in different countries, inform non-government and research organizations about the country-specific media audience profiles, and inform individuals to reflect on our day-to-day media diet.
"Connected to the people": Social Inclusion & Cohesion in Action through a Cultural Heritage Digital Tool
Authors: Nisi Valentina , Bala Paulo , Cesário Vanessa , James Stuart , Del Bue Alessio , Nunes Nuno Jardim
Published: October 2023

Current cultural policies are evolving from social inclusion (removing barriers and promoting equality for participation in culture) to social cohesion (fostering solid bonds between groups despite their differences). Digital interventions can create spaces that promote social inclusion and cohesion. In this paper, we report on the design and evaluation of a cultural heritage and digital storytelling application supporting a participatory approach to culture and hosting society. We evaluate our intervention in three marginalized communities with different social-cultural contexts: migrant women in Barcelona, a community living in a priority neighbourhood in Paris and second and third-generation migrants in Lisbon. Through an analysis of their application use, our findings point at their needs and desires, highlighting how the app can support social inclusion as the first step towards cohesion, but that these are heterogeneous concepts susceptible to nuanced appropriations by the different communities.
"I don't know how to help with that" - Learning from Limitations of Modern Conversational Agent Systems in Caregiving Networks
Authors: Zubatiy Tamara , Mathur Niharika , Heck Larry , Vickers Kayci L. , Rozga Agata , Mynatt Elizabeth D.
Published: October 2023

While commercial conversational agents (CA) (i.e. Google assistant, Siri, Alexa) are widely used, these systems have limitations in error-handling, flexibility, personalization and overall dialogue management that are amplified in care coordination settings. In this paper, we synthesize and articulate these limitations through quantitative and qualitative analysis of 56 older adults interacting with a commercial CA deployed in their home for a 10 week period. We look at the CA as a compensatory technology in an older adult's care network. We argue that the CA limitations are rooted in the rigid cue-and-response style of task-oriented interactions common in CAs. We then propose a redesign for CA conversation flow to favor flexibility and personalization that is nonetheless viable within the limitations of current AI and machine learning technologies. We explore design tradeoffs to better support the usability needs of older adults compared to current design optimizations driven by efficiency and privacy goals.
Are We Equal Online?: An Investigation of Gendered Language Patterns and Message Engagement on Enterprise Communication Platforms
Authors: Ferguson Sharon A. , Olechowski Alison
Published: October 2023

It was previously hypothesized that gender differences -- and thus gender discrimination -- would disappear if communication was no longer in person, and instead was transmitted and received in the same format for all. Yet, even online, researchers have identified gendered language styles in written communication that reveal gender cues and can lead to unequal treatment. In this work, we revisit these past findings and ask whether the same gendered patterns can be found on modern communication platforms, which present a new set of engagement features and mixed synchronous capabilities. We quantitatively analyze 335,000 Slack messages sent by 845 individuals as part of 46 teams, collected over six years of a product design capstone course. We found little evidence of traditionally gendered communication styles (characterized as elaborate, uncertain, and supportive) from the minority-gender participants. We did identify relationships between message author gender, communication style, and message engagement --- women and minority genders were more likely to have their messages engaged with, but only when using certain communication styles --- suggesting complex power dynamics exist on these platforms. We contribute the first study of gendered language styles on Enterprise Communication Platforms, adding to the community's understanding of how new settings and emerging technology relate to team collaborative dynamics, and motivating future tool development to support collaboration in diverse teams.
Can Synchronous Code Editing and Awareness Tools Support Remote Tutoring? Effects on Learning and Teaching
Authors: Yang Stephanie , Poonawala Amreen Amin , Jiang Tian-Shun Allan , Schneider Bertrand
Published: October 2023

One-on-one tutoring is effective for learning computer science since a tutor can work alongside a student and provide tailored feedback on their code. However, translating this type of instruction to a remote setting is challenging. Traditional methods such as screensharing lack key pedagogical functionality and most available tools are designed for collaboration rather than instruction. To identify tools that can support remote tutoring, we conducted an experiment to assess two resources: synchronous editing and awareness tools. In our study, an instructor teaches a learner introductory programming concepts remotely, collaborating through screensharing alone, a shared notebook with real-time collaborative editing, or a shared notebook with additional awareness tools overlaid. To embed the awareness tools, we designed a Chrome extension that enables real-time sharing of gaze and cursor data. Our results show that synchronous editing combined with awareness tools significantly improved learning. The awareness tools also helped tutors better communicate with the student, track their understanding, and establish a sense of presence. As a final contribution, we also assessed the efficacy of gaze-sharing using a webcam eye-tracker. While the accuracy was not as precise as a dedicated sensor, instructors described instances when the gaze was useful for gauging student attention and establishing presence. We discuss implications for remote tutoring in computer science and scaling awareness technology.
Contextual Gaps in Machine Learning for Mental Illness Prediction: The Case of Diagnostic Disclosures
Authors: Chancellor Stevie , Feuston Jessica L. , Chang Jayhyun
Published: October 2023

Getting training data for machine learning (ML) prediction of mental illness on social media data is labor intensive. To work around this, ML teams will extrapolate proxy signals, or alternative signs from data to evaluate illness status and create training datasets. However, these signals' validity has not been determined, whether signals align with important contextual factors, and how proxy quality impacts downstream model integrity. We use ML and qualitative methods to evaluate whether a popular proxy signal, diagnostic self-disclosure, produces a conceptually sound ML model of mental illness. Our findings identify major conceptual errors only seen through a qualitative investigation -- training data built from diagnostic disclosures encodes a narrow vision of diagnosis experiences that propagates into paradoxes in the downstream ML model. This gap is obscured by strong performance of the ML classifier (F1 = 0.91). We discuss the implications of conceptual gaps in creating training data for human-centered models, and make suggestions for improving research methods.
"Contradiction pushes me to improvise": Performer Expressivity and Engagement in Distanced Movement Performance Paradigms
Authors: LC Ray , Man Sihuang , Bao Xiying , Wan Jinhan , Wen Bo , Song Zijing
Published: October 2023

The virtualization of traditionally in-person experiences has altered the workflows of performing arts communities, resulting in modifications to performance venues and alterations to expressiveness and interaction. 25 professional movement-based performers who have participated in both live and online performances were interviewed in order to determine how virtualization processes affected their practices and how they adapted to these changes. We discovered that performers viewed online performances as time-limited, non-interactive film recordings. Instead of avoiding distant venues, performers adapted to new limitations, inventing improvisation strategies in distracting environments and using time and technological constraints as creative constraints. To investigate how a distanced paradigm affects the live-action workflow of dancers, we staged a performance in which a dancer interacted with a robot in a remote location. The case study demonstrated that the performer modified her rehearsal techniques to work with remote technology and adapted to live interaction with a remote audience by visualizing unseen interactions. This study provides guidance for the design of interactive technology for virtual performances, taking into account the adaptation strategies that performers are currently employing to circumvent limitations of time, location, and absence.
Crowdsourcing Subjective Annotations Using Pairwise Comparisons Reduces Bias and Error Compared to the Majority-vote Method
Authors: Narimanzadeh Hasti , Badie-Modiri Arash , Smirnova Iuliia G. , Chen Ted Hsuan Yun
Published: October 2023

How to better reduce measurement variability and bias introduced by subjectivity in crowdsourced labelling remains an open question. We introduce a theoretical framework for understanding how random error and measurement bias enter into crowdsourced annotations of subjective constructs. We then propose a pipeline that combines pairwise comparison labelling with Elo scoring, and demonstrate that it outperforms the ubiquitous majority-voting method in reducing both types of measurement error. To assess the performance of the labelling approaches, we constructed an agent-based model of crowdsourced labelling that lets us introduce different types of subjectivity into the tasks. We find that under most conditions with task subjectivity, the comparison approach produced higher f1 scores. Further, the comparison approach is less susceptible to inflating bias, which majority voting tends to do. To facilitate applications, we show with simulated and real-world data that the number of required random comparisons for the same classification accuracy scales log-linearly O(N log N) with the number of labelled items. We also implemented the Elo system as an open-source Python package.
Cultivating Altruism Around Computing Resources: Anticipation Work in a Scholarly Community
Authors: Cohoon Johanna , Kabir Kazi Sinthia , Motahar Tamanna , Wiese Jason
Published: October 2023

User research for scientific software can inform design and account for the unique concerns of academic researchers. In this study, we explored the user experience on a testbed for cloud computing research, CloudLab. Through 15 semi-structured interviews and observation, we observed the importance of time as a resource to system users. We observed CloudLab users strategically coordinating their time on the platform with other users, navigating the constraints of publication and other academic deadlines. Surprisingly, we found that this coordination may involve altruistic behaviors where users share time on CloudLab that had been allocated for personal use. In light of prior CSCW literature on how actors seek to harness time, we propose concrete opportunities for design interventions. Our strategy across all possible interventions is to increase users' awareness of the rhythms affecting their peers' platform use, allowing coordination based not just on knowledge of CloudLab reservations but also users' progress toward deadlines. The implications of this work inform the design of other similar cyberinfrastructure systems in science where users independently coordinate use of resources.
Designing a Direct Feedback Loop between Humans and Convolutional Neural Networks through Local Explanations
Authors: Sun Tong Steven , Gao Yuyang , Khaladkar Shubham , Liu Sijia , Zhao Liang , Kim Young-Ho , Hong Sungsoo Ray
Published: October 2023

The local explanation provides heatmaps on images to explain how Convolutional Neural Networks (CNNs) derive their output. Due to its visual straightforwardness, the method has been one of the most popular explainable AI (XAI) methods for diagnosing CNNs. Through our formative study (S1), however, we captured ML engineers' ambivalent perspective about the local explanation as a valuable and indispensable envision in building CNNs versus the process that exhausts them due to the heuristic nature of detecting vulnerability. Moreover, steering the CNNs based on the vulnerability learned from the diagnosis seemed highly challenging. To mitigate the gap, we designed DeepFuse, the first interactive design that realizes the direct feedback loop between a user and CNNs in diagnosing and revising CNN's vulnerability using local explanations. DeepFuse helps CNN engineers to systemically search "unreasonable" local explanations and annotate the new boundaries for those identified as unreasonable in a labor-efficient manner. Next, it steers the model based on the given annotation such that the model doesn't introduce similar mistakes. We conducted a two-day study (S2) with 12 experienced CNN engineers. Using DeepFuse, participants made a more accurate and "reasonable" model than the current state-of-the-art. Also, participants found the way DeepFuse guides case-based reasoning can practically improve their current practice. We provide implications for design that explain how future HCI-driven design can move our practice forward to make XAI-driven insights more actionable.
GuesSync!: An Online Casual Game To Reduce Affective Polarization
Authors: Rajadesingan Ashwin , Choo Daniel , Zhang Jessica , Inakage Mia , Budak Ceren , Resnick Paul
Published: October 2023

The past decade in the US has been one of the most politically polarizing in recent memory. Ordinary Democrats and Republicans fundamentally dislike and distrust each other, even when they agree on policy issues. This increase in hostility towards opposing party supporters, commonly called affective polarization, has important ramifications that threaten democracy. Political science research suggests that at least part of this polarization stems from Democrats' misperceptions about Republicans' political views and vice-versa. Therefore, in this work, drawing on insights from political science and game studies research, we designed an online casual game that combines the relaxed, playful nonpartisan norms of casual games with corrective information about party supporters' political views that are often misperceived. Through an experiment, we found that playing the game significantly reduces negative feelings toward outparty supporters among Democrats, but not Republicans. It was also effective in improving willingness to talk politics with outparty supporters. Further, we identified psychological reactance as a potential mechanism that affects the effectiveness of depolarization interventions. Finally, our analyses suggest that the game versions with political content were rated to be just as fun to play as a game version without any political content suggesting that, contrary to popular belief, people do like to mix politics and play.
Marginalization and the Construction of Mental Illness Narratives Online: Foregrounding Institutions in Technology-Mediated Care
Authors: Pendse Sachin R. , Kumar Neha , De Choudhury Munmun
Published: October 2023

People experiencing mental illness are often forced into a system in which their chances of finding relief are largely determined by institutions that evaluate whether their distress deserves treatment. These governing institutions can be offline, such as the American healthcare system, and can also be online, such as online social platforms. As work in Human-Computer Interaction (HCI) and Computer Supported Cooperative Work (CSCW) frames technology-mediated support as one method to fill structural gaps in care, in this study, we ask the question: how do online and offline institutions influence how people in resource-scarce areas understand and express their distress online? We situate our work in U.S. Mental Health Professional Shortage Areas (MHPSAs), or areas in which there are too few mental health professionals to meet expected needs. We use an analysis of illness narratives to answer this question, conducting a large scale linguistic analysis of social media posts to understand broader trends in expressions of distress online. We then build on these analyses via in-depth interviews with 18 participants with lived experience of mental illness, analyzing the role of online and offline institutions in how participants express distress online. Through our findings, we argue that a consideration of institutions is crucial in designing effective technology-mediated support, and discuss the implications of considering institutions in mental health support for platform designers.
Peer Produced Friction: How Page Protection on Wikipedia Affects Editor Engagement and Concentration
Authors: Ajmani Leah , Vincent Nicholas , Chancellor Stevie
Published: October 2023

Peer production systems have frictions-mechanisms that make contributing more effortful-to prevent vandalism and protect information quality. Page protection on Wikipedia is a mechanism where the platform's core values conflict, but there is little quantitative work to ground deliberation. In this paper, we empirically explore the consequences of page protection on Internet Culture articles on Wikipedia (6,264 articles, 108 edit-protected). We first qualitatively analyzed 150 requests for page protection, finding that page protection is motivated by an article's (1) activity, (2) topic area, and (3) visibility. These findings informed a matching approach to compare protected pages and similar unprotected articles. We quantitatively evaluate the differences between protected and unprotected pages across two dimensions: editor engagement and contributor concentration. Protected articles show different trends in editor engagement and equity amongst contributors, affecting the overall disparity in the population. We discuss the role of friction in online platforms, new ways to measure it, and future work.
Plan For Tomorrow: The Experience of Adolescent and Young Adult Childhood Cancer Survivors as they Transition to Adult Care
Authors: Ankrah Elizabeth A. , Marathe Megh , Bhattacharya Arpita , Ritt-Olson Anamara , Milam Joel E. , Torno Lilibeth , Hayes Gillian R.
Published: October 2023

Access to and understanding one's medical history is crucial to maintaining long-term care. As adolescents and young adults childhood cancer survivors age, they must transition and transfer their health care from their pediatric to an adult care institution. In this study, we provide empirical evidence reporting on the after-cancer treatment experiences of childhood cancer survivors through their transition. We report findings from 24 semi-structured interviews with adolescent and young adult cancer survivors participating in a childhood cancer survivorship program that prepares them for adult care. Our findings reveal three parts of their after-cancer treatment experience: the assumption of responsibility for their complex care needs and medical information and the overall transfer and maintenance of the continuity of their care to an adult clinician. Our findings suggest that survivors may play an essential yet unrecognized role in the patient hand-off. Thus, we introduce patient-mediate handoffs and suggest design opportunities.
Public Health Calls for/with AI: An Ethnographic Perspective
Authors: Ismail Azra , Thakkar Divy , Madhiwalla Neha , Kumar Neha
Published: October 2023

Artificial Intelligence (AI) based technologies are increasingly being integrated into public sector programs to help with decision-support and effective distribution of constrained resources. The field of Computer Supported Cooperative Work (CSCW) has begun to examine how the resultant sociotechnical systems may be designed appropriately when targeting underserved populations. We present an ethnographic study of a large-scale real-world integration of an AI system for resource allocation in a call-based maternal and child health program in India. Our findings uncover complexities around determining who benefits from the intervention, how the human-AI collaboration is managed, when intervention must take place in alignment with various priorities, and why the AI is sought, for what purpose. Our paper offers takeaways for human-centered AI integration in public health, drawing attention to the work done by the AI as actor, the work of configuring the human-AI partnership with multiple diverse stakeholders, and the work of aligning program goals for design and implementation through continual dialogue across stakeholders.
Refugee Entrepreneurial Trajectories
Authors: Lee Chuike , Viller Stephen , Vyas Dhaval
Published: October 2023

The global population of refugees as recorded by UNHCR is at an all-time high of over 90 million people forced to find new homes in a foreign land. Starting a new life can be unsettling for refugees and asylum seekers during the resettling process in their host countries, particularly when it comes to gaining financial independence. This paper used an interview-based study to engage with fifteen refugees and asylum seekers to learn how they achieve entrepreneurial success as they navigate refugee specific barriers in a new economy. The insights showed refugee entrepreneur specific barriers that align with resettlement challenges and the technical and social resourcefulness of this under-resourced community. Our contributions to the CSCW research community are an understanding of how low-socioeconomic entrepreneurs such as refugees, function in their ecosystem and design implications for developing technology to further the efforts of refugee entrepreneurs.
Reopening, Repetition and Resetting: HCI and the Method of Hope
Authors: Ratto Matt , Jackson Steven J.
Published: October 2023

This paper attempts to (re)theorize the nature and role of hope in collaborative and interventionist CSCW and HCI projects. Building on work in anthropology, STS, CSCW and HCI, and extended reflection on the 3Dprintability project - a multinational collaboration dedicated to the 3D printing of prosthetics in sub-Saharan Africa and Southeast Asia - it advocates for a more pluralistic and action-oriented understanding of hope built around moments of collaborative reopening, repetition and resetting. It then argues for a more robust and open-ended HCI method of hope that can change the way interventionist projects are conceived, documented, evaluated, and communicated, both in the HCI literature and in more public-facing accounts.
Sensing Wellbeing in the Workplace, Why and For Whom? Envisioning Impacts with Organizational Stakeholders
Authors: Kawakami Anna , Chowdhary Shreya , Iqbal Shamsi T. , Liao Q. Vera , Olteanu Alexandra , Suh Jina , Saha Koustuv
Published: October 2023

With the heightened digitization of the workplace, alongside the rise of remote and hybrid work prompted by the pandemic, there is growing corporate interest in using passive sensing technologies for workplace wellbeing. Existing research on these technologies often focus on understanding or improving interactions between an individual user and the technology. Workplace settings can, however, introduce a range of complexities that challenge the potential impact and in-practice desirability of wellbeing sensing technologies. Today, there is an inadequate empirical understanding of how everyday workers---including those who are impacted by, and impact the deployment of workplace technologies--envision its broader socio-ecological impacts. In this study, we conduct storyboard-driven interviews with 33 participants across three stakeholder groups: organizational governors, AI builders, and worker data subjects. Overall, our findings surface how workers envisioned wellbeing sensing technologies may lead to cascading impacts on their broader organizational culture, interpersonal relationships with colleagues, and individual day-to-day lives. Participants anticipated harms arising from ambiguity and misalignment around scaled notions of "worker wellbeing,'' underlying technical limitations to workplace-situated sensing, and assumptions regarding how social structures and relationships may shape the impacts and use of these technologies. Based on our findings, we discuss implications for designing worker-centered data-driven wellbeing technologies.
Social Wormholes: Exploring Preferences and Opportunities for Distributed and Physically-Grounded Social Connections
Authors: Leong Joanne , Teng Yuanyang , Liu Xingyu "Bruce" , Jun Hanseul , Kratz Sven , Tham Yu Jiang , Monroy-Hernández Andrés , Smith Brian A. , Vaish Rajan
Published: October 2023

Ubiquitous computing encapsulates the idea for technology to be interwoven into the fabric of everyday life. As computing blends into everyday physical artifacts, powerful opportunities open up for social connection. Prior connected media objects span a broad spectrum of design combinations. Such diversity suggests that people have varying needs and preferences for staying connected to one another. However, since these designs have largely been studied in isolation, we do not have a holistic understanding around how people would configure and behave within a ubiquitous social ecosystem of physically-grounded artifacts. In this paper, we create a technology probe called Social Wormholes, that lets people configure their own home ecosystem of connected artifacts. Through a field study with 24 participants, we report on patterns of behaviors that emerged naturally in the context of their daily lives and shine a light on how ubiquitous computing could be leveraged for social computing.
Sociotechnical Audits: Broadening the Algorithm Auditing Lens to Investigate Targeted Advertising
Authors: Lam Michelle S. , Pandit Ayush , Kalicki Colin H. , Gupta Rachit , Sahoo Poonam , Metaxa Danaë
Published: October 2023

Algorithm audits are powerful tools for studying black-box systems without direct knowledge of their inner workings. While very effective in examining technical components, the method stops short of a sociotechnical frame, which would also consider users themselves as an integral and dynamic part of the system. Addressing this limitation, we propose the concept of sociotechnical auditing: auditing methods that evaluate algorithmic systems at the sociotechnical level, focusing on the interplay between algorithms and users as each impacts the other. Just as algorithm audits probe an algorithm with varied inputs and observe outputs, a sociotechnical audit (STA) additionally probes users, exposing them to different algorithmic behavior and measuring their resulting attitudes and behaviors. As an example of this method, we develop Intervenr, a platform for conducting browser-based, longitudinal sociotechnical audits with consenting, compensated participants. Intervenr investigates the algorithmic content users encounter online, and also coordinates systematic client-side interventions to understand how users change in response. As a case study, we deploy Intervenr in a two-week sociotechnical audit of online advertising (N = 244) to investigate the central premise that personalized ad targeting is more effective on users. In the first week, we observe and collect all browser ads delivered to users, and in the second, we deploy an ablation-style intervention that disrupts normal targeting by randomly pairing participants and swapping all their ads. We collect user-oriented metrics (self-reported ad interest and feeling of representation) and advertiser-oriented metrics (ad views, clicks, and recognition) throughout, along with a total of over 500,000 ads. Our STA finds that targeted ads indeed perform better with users, but also that users begin to acclimate to different ads in only a week, casting doubt on the primacy of personalized ad targeting given the impact of repeated exposure. In comparison with other evaluation methods that only study technical components, or only experiment on users, sociotechnical audits evaluate sociotechnical systems through the interplay of their technical and human components.
Speculating with Care: Worker-centered Perspectives on Scale in a Chat-based Health Information Service
Authors: Karusala Naveena , Yan Shirley , Rajkumar Nupoor , G Victoria , Anderson Richard
Published: October 2023

Seeking to address barriers to in-person care, governments and non-governmental organizations (NGOs) globally have been pushing for scaling chat- or phone-based information services that rely on care workers to engage with users. Despite theoretical tensions between care and scale and the essential role of care workers, workers' perspective on scale and its impact on care provision is rarely centered early on in decisions to scale. In this paper, we examine care and scale from the perspective of medical support executives (MSEs) who support a chat-based health information service for maternal and child health deployed across multiple states in India. We draw on observations of MSEs' work, interviews with MSEs, NGO staff who implement the service, and families who use the service, and speculative design sessions conducted with MSEs. We find that by centering MSEs' perspectives, we can differentiate between growth of the relationships and heterogeneity that enable social impact, versus scale-thinking that promotes the decontextualization of care. We leverage our findings to discuss implications for scale and automation in chat-based health information services, including the importance of human connection, place, and support for care workers.
Tensions in Data Journey Activities: Mobilising, Processing, Producing, and Re-purposing Data in Environmental Assessment Practice
Authors: Jensen Rikke Hagensby , Johansen Stine S. , Hansen Nicolai Brodersen , Zada Ashna Mahmood , Nielsen Peter Axel
Published: October 2023

Digital data shape work practices as they travel through space, time, and social situations. In turn, workers shape the materiality of data through different data-oriented activities. In this paper, we draw on theory of data journeys to develop and present a conceptual framework of four data-intensive activities: Producing, mobilising, processing, and re-purposing. Together, those activities capture entanglements of data transformations and data-intensive practices. We develop the framework through a qualitative study of digitisation in Environmental Assessment (EA) practice. EA practitioners reflect on their experiences working with digital environmental data through ten semi-structured and two interactive interviews. The paper offers two main contributions. First, we develop a data journey theoretical framework and show that it is useful as a unit of analysis for uncovering tensions in data-oriented activities. Second, we use these insights to outline a set of tensions for future design activities in the area of data work practices.
Towards Equitable Online Participation: A Case of Older Adult Content Creators' Role Transition on Short-form Video Sharing Platforms
Authors: Tang Xinru , Ding Xianghua (Sharon) , Zhou Zhixuan
Published: October 2023

Short-form video sharing platforms (SVSPs) have seen a significant surge in older adult content creators in recent years. This emerging trend adds evidence to challenge the conventional perception of older adults as later technology adopters and passive online recipients. To investigate the reason behind the trend, we conducted semi-structured interviews with 13 older adult content creators on two of the most popular SVSPs in China, DouYin and KuaiShou. We found that our participants were initially attracted to SVSPs because of perceived ease of participation and the enjoyment they found. However, what kept them engaged was the attention and support they received there. SVSPs offered a low-barrier and equitable platform through their near-automatic use and relatively equal opportunities for recommendations, allowing everyone to reach audiences. Motivated by their passion for performance and the viewers' support, our participants actively acquired new skills for better performance and became more deeply involved on the platforms. Based on the findings, we reflect on how SVSPs' technical affordances support older adults in the transition from lurkers to contributors. We advocate for participation equity and supportive environments to promote more inclusive social media platforms.
Understanding Design Collaboration Between Designers and Artificial Intelligence: A Systematic Literature Review
Authors: Shi Yang , Gao Tian , Jiao Xiaohan , Cao Nan
Published: October 2023

Recent interest in design through the artificial intelligence (AI) lens is rapidly increasing. Designers, as a special user group interacting with AI, have received more attention in the Human-Computer Interaction community. Prior work has discussed emerging challenges that persist in designing for AI. However, few systematic reviews focus on AI for design to understand how designers and AI can augment each other's complementary strengths in design collaboration. In this work, we conducted a landscape analysis of AI for design, via a systematic literature review of 93 papers. The analysis first provides a bird's eye view of overall patterns in this area. The analysis also reveals three themes interpreted from the paper corpus associated with AI for design, including AI assisting designers, designers assisting AI, and characterizing designer-AI collaboration. We discuss the implications of our findings and suggested methodological proposals to guide HCI toward research and practices that center on collaborative creativity.
What is a File on a Phone? Personal Information Management Practices Amongst WhatsApp Users
Authors: Adavi Krishna Akhil Kumar , Acker Amelia
Published: October 2023

The file, as a means of sharing structured information across time and place, has spanned centuries of ICTs. Despite much CSCW research on file management practices in organizational desktop computing settings, little research has examined how files are managed and shared using mobile devices. Our research asks, how do mobile phones and mobile applications impact the personal information management (PIM) practices involving files for young adults? In this interview and task observation study, we examined the file management practices of mobile phone users (N=25), both Android and iOS owners who use the superapp WhatsApp. Superapps like WeChat and WhatsApp are increasingly characterized as technology of life for the majority world, particularly among mobile-first users. We find that many grammars of action related to managing digital files in personal computing and email contexts persist, but participants' sharing practices are influenced by media ideologies of friends, family, colleagues; and that their file management practices are shaped by the affordances of WhatsApp, as well as mobile operating systems and device hardware constraints. These results will be useful to researchers examining collective PIM practices; mobile communication practices between users and businesses via messaging apps; and theories of personal information practices related to the sharing and storage of digital files among mobile-first cohorts who increasingly share and access information via platforms and mobile applications.
Suspecting Sarcasm: How League of Legends Players Dismiss Positive Communication in Toxic Environments
Authors: Poeller Susanne , Dechant Martin Johannes , Klarkowski Madison , Mandryk Regan L.
Published: October 2023

Toxicity in multiplayer gaming is an ongoing problem that threatens the well-being of players, gaming communities, and game developers. Meanwhile, interventions that promote positive interactions and proactively create positive gaming spaces are still in their infancy; little is known about how players respond to positivity.
In our study, 959 League of Legends players were presented with either 10 positive chat logs or 10 negative chat logs, and asked to reflect on the content and how representative such communication is of their own gaming experiences. We thematically coded participants' free-form answers (identifying the themes normalize, acknowledge, downplay, cope, blame, and make personal), and compared the positive and negative conditions in terms of theme prevalence. Our findings show that participants were more likely to normalize and acknowledge toxic negativity than positivity. Furthermore, the dominant response to positivity consisted of downplaying messages as not representative and rare, and even expressing suspicion that messages must have been fabricated or intended as sarcasm. Participants overwhelmingly cope by muting chat, protecting them from toxic interactions, but leaving them unexposed to positive communication and other beneficial social interactions within play.
Small Latency Variations Do Not Affect Player Performance in First-Person Shooters
Authors: Schmid Andreas , Halbhuber David , Fischer Thomas , Wimmer Raphael , Henze Niels
Published: October 2023

In interactive systems high latency affects user performance and experience. This is especially problematic in video games. A large number of studies on this topic investigated the effects of constant, high latency. However, in practice, latency is never constant but varies by up to 100 ms due to variations in processing time and delays added by polling between system components. In a large majority of studies, these variations in latency are neither controlled for nor reported. Thus, it is unclear to which degree small, continuous variations in latency affect user performance. If these unreported variations had a significant impact, this might cast into doubt the findings of some studies. To investigate how latency variation affects player performance and experience in games, we conducted an experiment with 28 participants playing a first-person shooter. Participants played with two levels of base latency (50 ms vs. 150 ms) and variation (0 ms vs. 50 ms). As expected, high base latency significantly reduces player performance and experience. However, we found strong evidence that small variations in latency in the order of 50 ms, do not affect player performance significantly. Thus, our findings mitigate concerns that previous latency studies might have systematically ignored a confounding effect.