huashen218/convxai-cia-dataset huggingface dataset:
Title: More Kawaii than a Real-Person Live Streamer: Understanding How the Otaku Community Engages with and Perceives Virtual YouTubers
Authors: family: Lu
given: Zhicong; family: Shen
given: Chenxinran; family: Li
given: Jiannan; family: Shen
given: Hong; family: Wigdor
given: Daniel
Venue: Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems
Keywords: user engagement, virtual idols, live streaming, social media, virtual YouTuber

Abstract: Live streaming has become increasingly popular, with most streamers presenting their real-life appearance. However, Virtual YouTubers (VTubers), virtual 2D or 3D avatars that are voiced by humans, are emerging as live streamers and attracting a growing viewership in East Asia. Although prior research has found that many viewers seek real-life interpersonal interactions with real-person streamers, it is currently unknown what makes VTuber live streams engaging or how they are perceived differently than real-person streamers. We conducted an interview study to understand how viewers engage with VTubers and perceive the identities of the voice actors behind the avatars (i.e., Nakanohito). The data revealed that Virtual avatars bring unique performative opportunities which result in different viewer expectations and interpretations of VTuber behavior. Viewers intentionally upheld the disembodiment of VTuber avatars from their voice actors. We uncover the nuances in viewer perceptions and attitudes and further discuss the implications of VTuber practices to the understanding of live streaming in general.
Title: Who Is Included in Human Perceptions of AI?: Trust and Perceived Fairness around Healthcare AI and Cultural Mistrust
Authors: family: Lee
given: Min Kyung; family: Rich
given: Katherine
Venue: Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems
Keywords: Fairness, Group-Based Medical Mistrust Scale (GBMMS), Healthcare AI, Perceptions of Algorithmic Decisions, Black Perspectives, Trust

Abstract: Emerging research suggests that people trust algorithmic decisions less than human decisions. However, different populations, particularly in marginalized communities, may have different levels of trust in human decision-makers. Do people who mistrust human decision-makers perceive human decisions to be more trustworthy and fairer than algorithmic decisions? Or do they trust algorithmic decisions as much as or more than human decisions? We examine the role of mistrust in human systems in people’s perceptions of algorithmic decisions. We focus on healthcare Artificial Intelligence (AI), group-based medical mistrust, and Black people in the United States. We conducted a between-subjects online experiment to examine people’s perceptions of skin cancer screening decisions made by an AI versus a human physician depending on their medical mistrust, and we conducted interviews to understand how to cultivate trust in healthcare AI. Our findings highlight that research around human experiences of AI should consider critical differences in social groups.
Title: An Examination of the Work Practices of Crowdfarms
Authors: family: Wang
given: Yihong; family: Papangelis
given: Konstantinos; family: Saker
given: Michel; family: Lykourentzou
given: Ioanna; family: Khan
given: Vassilis-Javed; family: Chamberlain
given: Alan; family: Grudin
given: Jonathan
Venue: Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems
Keywords: Work Practices, Crowdsourcing, Crowdfarms

Abstract: Crowdsourcing is a new value creation business model. Annual revenue of the Chinese market alone is hundreds of millions of dollars, yet few studies have focused on the practices of the Chinese crowdsourcing workforce, and those that do mainly focus on solo crowdworkers. We have extended our study of solo crowdworker practices to include crowdfarms, a relatively new entry to the gig economy: small companies that carry out crowdwork as a key part of their business. We report here on interviews of people who work in 53 crowdfarms. We describe how crowdfarms procure jobs, carry out macrotasks and microtasks, manage their reputation, and employ different management practices to motivate crowdworkers and customers.
Title: The Labor of Fun: Understanding the Social Relationships between Gamers and Paid Gaming Teammates in China
Authors: family: Shen
given: Chenxinran; family: Lu
given: Zhicong; family: Faas
given: Travis; family: Wigdor
given: Daniel
Venue: Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems
Keywords: social networking, gamers, online community, social relationships, social media, gaming

Abstract: Online video games support the development of social relationships through gameplay, however, gamers often cannot cultivate and maintain relationships based on social factors such as personality when using in-game matchmaking services. To address this, teammate matching sites external to games have emerged and enable gamers to offer to play games with others in exchange for payment. The affordances of these services are different from other existing gamer social sites, e.g., live streaming. Interviews were conducted with 16 dedicated users on Bixin, one of China’s largest paid teammate matching sites, to examine user motivations, practices, and perceptions. The interviews found that gamers selected paid teammates on Bixin using different criteria compared to in-game matchmaking services and emphasized the importance of real-life characteristics such as voice. To maintain connections, paid teammates often also extended communication to external communication services such as WeChat. Although most gamers expected to communicate with paid teammates as if they were friends, very few reported building real friendships with their matched counterparts.
Title: Standardizing Reporting of Participant Compensation in HCI: A Systematic Literature Review and Recommendations for the Field
Authors: family: Pater
given: Jessica; family: Coupe
given: Amanda; family: Pfafman
given: Rachel; family: Phelan
given: Chanda; family: Toscos
given: Tammy; family: Jacobs
given: Maia
Venue: Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems
Keywords: UBICOMP/IMWUT, meta-review, UIST, CSCW, HCI, participant payment

Abstract: The user study is a fundamental method used in HCI. In designing user studies, we often use compensation strategies to incentivize recruitment. However, compensation can also lead to ethical issues, such as coercion. The CHI community has yet to establish best practices for participant compensation. Through a systematic review of manuscripts at CHI and other associated publication venues, we found high levels of variation in the compensation strategies used within the community and how we report on this aspect of the study methods. A qualitative analysis of justifications offered for compensation sheds light into how some researchers are currently contextualizing this practice. This paper provides a description of current compensation strategies and information that can inform the design of compensation strategies in future studies. The findings may be helpful to generate productive discourse in the HCI community towards the development of best practices for participant compensation in user studies.
Title: Can Online Juries Make Consistent, Repeatable Decisions?
Authors: family: Hu
given: Xinlan Emily; family: Whiting
given: Mark E; family: Bernstein
given: Michael S.
Venue: Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems
Keywords: Juries, Governance, Deliberation, Individuals, Groups

Abstract: A jury of one’s peers is a prominent way to adjudicate disputes and is increasingly used in participatory governance online. The fairness of this approach rests on the assumption that juries are consistent: that the same jury would hand down similar judgments to similar cases. However, prior literature suggests that social influence would instead cause early interactions to cascade into different judgments for similar cases. In this paper, we report an online experiment that changes participants’ pseudonyms as they appear to collaborators, temporarily masking a jury’s awareness that they have deliberated together before. This technique allows us to measure consistency by reconvening the same jury on similar cases. Counter to expectation, juries are equally consistent as individuals, a result that is “good for democracy.” But this consistency arises in part due to group polarization, as consensus develops by hardening initial majority opinions. Furthermore, we find that aggregating groups’ perspectives without deliberation erodes consistency.
Title: How WEIRD is CHI?
Authors: family: Linxen
given: Sebastian; family: Sturm
given: Christian; family: Brühlmann
given: Florian; family: Cassau
given: Vincent; family: Opwis
given: Klaus; family: Reinecke
given: Katharina
Venue: Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems
Keywords: sample bias, generalizability, HCI research, geographic diversity, WEIRD

Abstract: Computer technology is often designed in technology hubs in Western countries, invariably making it “WEIRD”, because it is based on the intuition, knowledge, and values of people who are Western, Educated, Industrialized, Rich, and Democratic. Developing technology that is universally useful and engaging requires knowledge about members of WEIRD and non-WEIRD societies alike. In other words, it requires us, the CHI community, to generate this knowledge by studying representative participant samples. To find out to what extent CHI participant samples are from Western societies, we analyzed papers published in the CHI proceedings between 2016-2020. Our findings show that 73% of CHI study findings are based on Western participant samples, representing less than 12% of the world’s population. Furthermore, we show that most participant samples at CHI tend to come from industrialized, rich, and democratic countries with generally highly educated populations. Encouragingly, recent years have seen a slight increase in non-Western samples and those that include several countries. We discuss suggestions for further broadening the international representation of CHI participant samples.
Title: Qualitative Secondary Analysis as an Alternative Approach for Cross-Cultural Design: A Case Study with Saudi transnationals
Authors: family: Alshehri
given: Taghreed; family: Abokhodair
given: Norah; family: Kirkham
given: Reuben; family: Olivier
given: Patrick
Venue: Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems
Keywords: Cross-Cultural Design, Qualitative Secondary Analysis (QSA), Culture

Abstract: It is widely acknowledged in HCI that culture is embodied in many aspects of an individual's identity and interaction with technology. Whilst existing cultural models have been criticized for providing a deterministic view of culture, alternative methods for incorporating culture in design remain scarce. We introduce the use of Qualitative Secondary Analysis (QSA) as a bottom-up approach to construct a richer and more dynamic understanding of culture to inform our best practices in Cross-Cultural Design. We demonstrate the use of QSA within a culturally specific context, namely Saudi transnationals. We draw upon two case studies (with 55 participants) to investigate the cultural factors underpinning our participants views. We conclude with a reflection on key affordances and challenges of QSA, illustrating how QSA can be leveraged to unravel otherwise overlooked knowledge present in many qualitative HCI studies.
Title: An Activity Theory Analysis of Search & Rescue Collective Sensemaking and Planning Practices
Authors: family: Alharthi
given: Sultan A.; family: LaLone
given: Nicolas James; family: Sharma
given: Hitesh Nidhi; family: Dolgov
given: Igor; family: Toups
given: Z O.
Venue: Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems
Keywords: search and rescue, planning, training, practice, maps, sensemaking, activity theory.

Abstract: Search and rescue (SAR), a disaster response activity performed to locate and save victims, primarily involves collective sensemaking and planning. SAR responders learn to search and navigate the environment, process information about buildings, and collaboratively plan with maps. We synthesize data from five sources, including field observations and interviews, to understand the informational components of SAR and how information is recorded and communicated. We apply activity theory, uncovering unforeseen factors that are relevant to the design of collaboration systems and training solutions. Through our analysis, we derive design implications to support collaborative information technology and training systems: mixing physical and digital mapping; mixing individual and collective mapping; building for different levels and sources of information; and building for different rules, roles, and activities.
Title: What Do Hackathons Do? Understanding Participation in Hackathons Through Program Theory Analysis
Authors: family: Falk
given: Jeanette; family: Kannabiran
given: Gopinaath; family: Hansen
given: Nicolai Brodersen
Venue: Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems
Keywords: hackathons, program theory, participatory design, research methods

Abstract: Hackathons are increasingly embraced across diverse sectors as a way of democratizing the design of technology. Several attempts have been made to redefine the format and desired end goal of hackathons in recent years thereby warranting closer methodological scrutiny. In this paper, we apply program theory to analyze the processes and effects of 16 hackathon case studies through published research literature. Building upon existing research on hackathons, our work offers a critical perspective examining the methodological validity of hackathons and exemplifies how specific processes for organizing hackathons are modified for different purposes. Our main contribution is a program theory analysis of hackathon formats that provides an exploration and juxtaposition of 16 case studies in terms of causal relations between the input, process and the effects of hackathons. Our cataloguing of examples can serve as an inspirational planning resource for future organizers of hackathons.
Title: When the Tab Comes Due:Challenges in the Cost Structure of Browser Tab Usage
Authors: family: Chang
given: Joseph Chee; family: Hahn
given: Nathan; family: Kim
given: Yongsung; family: Coupland
given: Julina; family: Breneisen
given: Bradley; family: Kim
given: Hannah S; family: Hwong
given: John; family: Kittur
given: Aniket
Venue: Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems
Keywords: world wide web, user behavior, browser interfaces, interviews, tabbed browsing, survey

Abstract: Tabs have become integral to browsing the Web yet have changed little since their introduction nearly 20 years ago. In contrast, the internet has gone through dramatic changes, with users increasingly moving from navigating to websites to exploring information across many sources to support online sensemaking. This paper investigates how tabs today are overloaded with a diverse set of functionalities and issues users face when managing them. We interviewed ten information workers asking about their tab management strategies and walk through each open tab on their work computers four times over two weeks. We uncovered competing pressures pushing for keeping tabs open (ranging from interaction to emotional costs) versus pushing for closing them (such as limited attention and resources). We then surveyed 103 participants to estimate the frequencies of these pressures at scale. Finally, we developed design implications for future browser interfaces that can better support managing these pressures.
Title: Towards the Right Direction in BiDirectional User Interfaces
Authors: family: Goldenberg
given: Yulia; family: Tractinsky
given: Noam
Venue: Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems
Keywords: Bidirectional interface, Bidirectional design, BiDi, UI element direction, Localization, Right-to-left design

Abstract: Hundreds of millions of speakers of bidirectional (BiDi) languages rely on writing systems that mix the native right-to-left script with left-to-right strings. The global reach of interactive digital technologies requires special attention to these people, whose perception of interfaces is affected by this script mixture. However, empirical research on this topic is scarce. Although leading software vendors provide guidelines for BiDi design, bidirectional interfaces demonstrate inconsistent and incorrect directionality of UI elements, which may cause user confusion and errors.Through a websites' review, we identified problematic UI items and considered reasons for their existence. In an online survey with 234 BiDi speakers, we observed that in many cases, users' direction preferences were inconsistent with the guidelines. The findings provide potential insights for design rules and empirical evidence for the problem's complexity, suggesting the need for further empirical research and greater attention by the HCI community to the BiDi design problem.
Title: PinpointFly: An Egocentric Position-control Drone Interface using Mobile AR
Authors: family: Chen
given: Linfeng; family: Takashima
given: Kazuki; family: Fujita
given: Kazuyuki; family: Kitamura
given: Yoshifumi
Venue: Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems
Keywords: Visualization, Spatial Perception, Videography, Positioning

Abstract: Accurate drone positioning is challenging because pilots only have a limited position and direction perception of a flying drone from their perspective. This makes conventional joystick-based speed control inaccurate and more complicated and significantly degrades piloting performance. We propose PinpointFly, an egocentric drone interface that allows pilots to arbitrarily position and rotate a drone using position-control direct interactions on a see-through mobile AR where the drone position and direction are visualized with a virtual cast shadow (i.e., the drone’s orthogonal projection onto the floor). Pilots can point to the next position or draw the drone’s flight trajectory by manipulating the virtual cast shadow and the direction/height slider bar on the touchscreen. We design and implement a prototype of PinpointFly for indoor and visual line of sight scenarios, which are comprised of real-time and predefined motion-control techniques. We conduct two user studies with simple positioning and inspection tasks. Our results demonstrate that PinpointFly makes the drone positioning and inspection operations faster, more accurate, simpler and fewer workload than a conventional joystick interface with a speed-control method.
Title: How Should AI Systems Talk to Users when Collecting their Personal Information? Effects of Role Framing and Self-Referencing on Human-AI Interaction
Authors: family: Liao
given: Mengqi; family: Sundar
given: S. Shyam
Venue: Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems
Keywords: power usage, Human-AI Interaction, social presence of AI, social cues

Abstract: AI systems collect our personal information in order to provide personalized services, raising privacy concerns and making users leery. As a result, systems have begun emphasizing overt over covert collection of information by directly asking users. This poses an important question for ethical interaction design, which is dedicated to improving user experience while promoting informed decision-making: Should the interface tout the benefits of information disclosure and frame itself as a help-provider? Or, should it appear as a help-seeker? We decided to find out by creating a mockup of a news recommendation system called Mindz and conducting an online user study (N=293) with the following four variations: AI system as help seeker vs. help provider vs. both vs. neither. Data showed that even though all participants received the same recommendations, power users tended to trust a help-seeking Mindz more whereas non-power users favored one that is both help-seeker and help-provider.
Title: Exploring and Promoting Diagnostic Transparency and Explainability in Online Symptom Checkers
Authors: family: Tsai
given: Chun-Hua; family: You
given: Yue; family: Gui
given: Xinning; family: Kou
given: Yubo; family: Carroll
given: John M.
Venue: Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems
Keywords: Explanation, Symptom Checker, Transparency, Health, COVID-19

Abstract: Online symptom checkers (OSC) are widely used intelligent systems in health contexts such as primary care, remote healthcare, and epidemic control. OSCs use algorithms such as machine learning to facilitate self-diagnosis and triage based on symptoms input by healthcare consumers. However, intelligent systems’ lack of transparency and comprehensibility could lead to unintended consequences such as misleading users, especially in high-stakes areas such as healthcare. In this paper, we attempt to enhance diagnostic transparency by augmenting OSCs with explanations. We first conducted an interview study (N=25) to specify user needs for explanations from users of existing OSCs. Then, we designed a COVID-19 OSC that was enhanced with three types of explanations. Our lab-controlled user study (N=20) found that explanations can significantly improve user experience in multiple aspects. We discuss how explanations are interwoven into conversation flow and present implications for future OSC designs.
Title: User Trust in Assisted Decision-Making Using Miniaturized Near-Infrared Spectroscopy
Authors: family: Jiang
given: Weiwei; family: Sarsenbayeva
given: Zhanna; family: van Berkel
given: Niels; family: Wang
given: Chaofan; family: Yu
given: Difeng; family: Wei
given: Jing; family: Goncalves
given: Jorge; family: Kostakos
given: Vassilis
Venue: Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems
Keywords: gluten, NIRS, mobile sensing, decision-making, trust.

Abstract: We investigate the use of a miniaturized Near-Infrared Spectroscopy (NIRS) device in an assisted decision-making task. We consider the real-world scenario of determining whether food contains gluten, and we investigate how end-users interact with our NIRS detection device to ultimately make this judgment. In particular, we explore the effects of different nutrition labels and representations of confidence on participants’ perception and trust. Our results show that participants tend to be conservative in their judgment and are willing to trust the device in the absence of understandable label information. We further identify strategies to increase user trust in the system. Our work contributes to the growing body of knowledge on how NIRS can be mass-appropriated for everyday sensing tasks, and how to enhance the trustworthiness of assisted decision-making systems.