huashen218/convxai-cia-dataset huggingface dataset:
Title: Bot or not? User Perceptions of Player Substitution with Deep Player Behavior Models
Authors: family: Pfau
given: Johannes; family: Smeddinck
given: Jan David; family: Bikas
given: Ioannis; family: Malaka
given: Rainer
Venue: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Abstract: Many online games suffer when players drop off due to lost connections or quitting prematurely, which leads to match terminations or game-play imbalances. While rule-based outcome evaluations or substitutions with bots are frequently used to mitigate such disruptions, these techniques are often perceived as unsatisfactory. Deep learning methods have successfully been used in deep player behavior modelling (DPBM) to produce non-player characters or bots which show more complex behavior patterns than those modelled using traditional AI techniques. Motivated by these findings, we present an investigation of the player-perceived awareness, believability and representativeness, when substituting disconnected players with DPBM agents in an online-multiplayer action game. Both quantitative and qualitative outcomes indicate that DPBM agent substitutes perform similarly to human players and that players were unable to detect substitutions. Notably, players were in fact able to detect substitution with agents driven by more traditional heuristics.
Title: Decoding Intent With Control Theory: Comparing Muscle Versus Manual Interface Performance
Authors: family: Yamagami
given: Momona; family: Steele
given: Katherine M.; family: Burden
given: Samuel A.
Venue: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Abstract: Manual device interaction requires precise coordination which may be difficult for users with motor impairments. Muscle interfaces provide alternative interaction methods that may enhance performance, but have not yet been evaluated for simple (eg. mouse tracking) and complex (eg. driving) continuous tasks. Control theory enables us to probe continuous task performance by separating user input into intent and error correction to quantify how motor impairments impact device interaction. We compared the effectiveness of a manual versus a muscle interface for eleven users without and three users with motor impairments performing continuous tasks. Both user groups preferred and performed better with the muscle versus the manual interface for the complex continuous task. These results suggest muscle interfaces and algorithms that can detect and augment user intent may be especially useful for future design of interfaces for continuous tasks.
Title: "All in the Same Boat": Tradeoffs of Voice Assistant Ownership for Mixed-Visual-Ability Families
Authors: family: Storer
given: Kevin M.; family: Judge
given: Tejinder K.; family: Branham
given: Stacy M.
Venue: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Abstract: A growing body of evidence suggests Voice Assistants (VAs) are highly valued by people with vision impairments (PWVI) and much less so by sighted users. Yet, many are deployed in homes where both PWVI and sighted family members reside. Researchers have yet to study whether VA use and perceived benefits are affected in settings where one person has a visual impairment and others do not. We conducted six in-depth interviews with partners to understand patterns of domestic VA use in mixed-visual-ability families. Although PWVI were more motivated to acquire VAs, used them more frequently, and learned more proactively about their features, partners with vision identified similar benefits and disadvantages of having VAs in their home. We found that the universal usability of VAs both equalizes experience across abilities and presents complex tradeoffs for families-regarding interpersonal relationships, domestic labor, and physical safety-which are weighed against accessibility benefits for PWVI and complicate the decision to fully integrate VAs in the home.
Title: An Interaction Design for Machine Teaching to Develop AI Tutors
Authors: family: Weitekamp
given: Daniel; family: Harpstead
given: Erik; family: Koedinger
given: Ken R.
Venue: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Abstract: Intelligent tutoring systems (ITSs) have consistently been shown to improve the educational outcomes of students when used alone or combined with traditional instruction. However, building an ITS is a time-consuming process which requires specialized knowledge of existing tools. Extant authoring methods, including the Cognitive Tutor Authoring Tools' (CTAT) example-tracing method and SimStudent's Authoring by Tutoring, use programming-by-demonstration to allow authors to build ITSs more quickly than they could by hand programming with model-tracing. Yet these methods still suffer from long authoring times or difficulty creating complete models. In this study, we demonstrate that Simulated Learners built with the Apprentice Learner (AL) Framework can be combined with a novel interaction design that emphasizes model transparency, input flexibility, and problem solving control to enable authors to achieve greater model completeness in less time than existing authoring methods.
Title: Unfabricate: Designing Smart Textiles for Disassembly
Authors: family: Wu
given: Shanel; family: Devendorf
given: Laura
Venue: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Abstract: Smart textiles development is combining computing and textile technologies to create tactile, functional objects such as smart garments, soft medical devices, and space suits. However, the field also combines the massive waste streams of both the digital electronics and textiles industries. The following work explores how HCI researchers might be poised to address sustainability and waste in future smart textiles development through interventions at design time. Specifically, we perform a design inquiry into techniques and practices for reclaiming and reusing smart textiles materials and explore how such techniques can be integrated into smart textiles design tools. Beginning with a practice in sustainable or "slow" fashion, unravelling a garment into yarn, the suite of explorations titled "Unfabricate" probes values of time and labor in crafting a garment; speculates how a smart textile garment may be designed with reuse in mind; and imagines how electronic and textile components may be given new life in novel uses.
Title: Bridging the Virtual and Real Worlds: A Preliminary Study of Messaging Notifications in Virtual Reality
Authors: family: Hsieh
given: Ching-Yu; family: Chiang
given: Yi-Shyuan; family: Chiu
given: Hung-Yu; family: Chang
given: Yung-Ju
Venue: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Abstract: Virtual reality (VR) platforms provide their users with immersive virtual environments, but disconnect them from real-world events. The increasing length of VR sessions can therefore be expected to boost users' needs to obtain information about external occurrences such as message arrival. Yet, how and when to present these real-world notifications to users engaged in VR activities remains underexplored. We conducted an experiment to investigate individuals' receptivity during four VR activities (Loading, 360 Video, Treasure Hunt, Rhythm Game) to message notifications delivered using three types of displays (head-mounted, controller, and movable panel). While higher engagement generally led to higher perceptions that notifications were ill-timed and/or disruptive, the suitability of notification displays to VR activities was influenced by the time-sensitiveness of VR content, overlapping use of modalities for delivering alerts, the display locations, and a requirement that the display be moved for notifications to be seen. Specific design suggestions are also provided.
Title: A Human-Centered Review of Algorithms used within the U.S. Child Welfare System
Authors: family: Saxena
given: Devansh; family: Badillo-Urquiola
given: Karla; family: Wisniewski
given: Pamela J.; family: Guha
given: Shion
Venue: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Abstract: The U.S. Child Welfare System (CWS) is charged with improving outcomes for foster youth; yet, they are overburdened and underfunded. To overcome this limitation, several states have turned towards algorithmic decision-making systems to reduce costs and determine better processes for improving CWS outcomes. Using a human-centered algorithmic design approach, we synthesize 50 peer-reviewed publications on computational systems used in CWS to assess how they were being developed, common characteristics of predictors used, as well as the target outcomes. We found that most of the literature has focused on risk assessment models but does not consider theoretical approaches (e.g., child-foster parent matching) nor the perspectives of caseworkers (e.g., case notes). Therefore, future algorithms should strive to be context-aware and theoretically robust by incorporating salient factors identified by past research. We provide the HCI community with research avenues for developing human-centered algorithms that redirect attention towards more equitable outcomes for CWS.
Title: In Search of Forms for Evocative and Generative Reflection: Exploratory Studies and a Design Proposal
Authors: family: Jung
given: Heekyoung
Venue: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Abstract: Today an increasing number of personal informatics tools and platforms support intended behavior change and goal achievement through data-based self-reflection. The scope of self-reflection expands with emerging sources, goals, and challenges of human well-being, demanding for reframing recent computer-mediated reflective practice. This study investigates a broader range of contexts and forms of self-reflection that support navigating one's mind and goals beyond achieving preset goals. This paper describes contemporary issues on human well-being and two exploratory studies-one conducted in a traveling artists' residency and the other in a design studio class-which surveyed various triggers, contexts, and forms of self-reflection. By connecting the insights from the two studies, I propose evocative and generative reflection as an alternative perspective to tracking-based, goal-oriented reflection and discuss implications for the design for reflection with a focus on the creative dimension of human well-being.
Title: Will the Crowd Game the Algorithm? Using Layperson Judgments to Combat Misinformation on Social Media by Downranking Distrusted Sources
Authors: family: Epstein
given: Ziv; family: Pennycook
given: Gordon; family: Rand
given: David
Venue: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Abstract: How can social media platforms fight the spread of misinformation? One possibility is to use newsfeed algorithms to downrank content from sources that users rate as untrustworthy. But will laypeople be handicapped by motivated reasoning or lack of expertise, and thus unable to identify misinformation sites? And will they "game" this crowdsourcing mechanism in order to promote content that aligns with their partisan agendas? We conducted a survey experiment in which =984 Americans indicated their trust in numerous news sites. To study the tendency of people to game the system, half of the participants were told their responses would inform social media ranking algorithms. Participants trusted mainstream sources much more than hyper-partisan or fake news sources, and their ratings were highly correlated with professional fact-checker judgments. Critically, informing participants that their responses would influence ranking algorithms did not diminish these results, despite the manipulation increasing the political polarization of trust ratings.
Title: BISHARE: Exploring Bidirectional Interactions Between Smartphones and Head-Mounted Augmented Reality
Authors: family: Zhu
given: Fengyuan; family: Grossman
given: Tovi
Venue: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Abstract: In pursuit of a future where HMD devices can be used in tandem with smartphones and other smart devices, we present BISHARE, a design space of cross-device interactions between smartphones and ARHMDs. Our design space is unique in that it is bidirectional in nature, as it examines how both the HMD can be used to enhance smartphone tasks, and how the smartphone can be used to enhance HMD tasks. We then present an interactive prototype that enables cross-device interactions across the proposed design space. A 12-participant user study demonstrates the promise of the design space and provides insights, observations, and guidance for the future.
Title: MagTouch: Robust Finger Identification for a Smartwatch Using a Magnet Ring and a Built-in Magnetometer
Authors: family: Park
given: Keunwoo; family: Kim
given: Daehwa; family: Heo
given: Seongkook; family: Lee
given: Geehyuk
Venue: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Abstract: Completing tasks on smartwatches often requires multiple gestures due to the small size of the touchscreens and the lack of sufficient number of touch controls that are easily accessible with a finger. We propose to increase the number of functions that can be triggered with the touch gesture by enabling a smartwatch to identify which finger is being used. We developed MagTouch, a method that uses a magnetometer embedded in an off-the-shelf smartwatch. It measures the magnetic field of a magnet fixed to a ring worn on the middle finger. By combining the measured magnetic field and the touch location on the screen, MagTouch recognizes which finger is being used. The tests demonstrated that MagTouch can differentiate among the three fingers used to make contacts at a success rate of 95.03%.
Title: Teddy: A System for Interactive Review Analysis
Authors: family: Zhang
given: Xiong; family: Engel
given: Jonathan; family: Evensen
given: Sara; family: Li
given: Yuliang; family: Demiralp
given: Çağatay; family: Tan
given: Wang-Chiew
Venue: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Abstract: Reviews are integral to e-commerce services and products. They contain a wealth of information about the opinions and experiences of users, which can help better understand consumer decisions and improve user experience with products and services. Today, data scientists analyze reviews by developing rules and models to extract, aggregate, and understand information embedded in the review text. However, working with thousands of reviews, which are typically noisy incomplete text, can be daunting without proper tools. Here we first contribute results from an interview study that we conducted with fifteen data scientists who work with review text, providing insights into their practices and challenges. Results suggest data scientists need interactive systems for many review analysis tasks. Towards a solution, we then introduce Teddy, an interactive system that enables data scientists to quickly obtain insights from reviews and improve their extraction and modeling pipelines.
Title: E-Textile Microinteractions: Augmenting Twist with Flick, Slide and Grasp Gestures for Soft Electronics
Authors: family: Olwal
given: Alex; family: Starner
given: Thad; family: Mainini
given: Gowa
Venue: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Abstract: E-textile microinteractions advance cord-based interfaces by enabling the simultaneous use of precise continuous control and casual discrete gestures. We leverage the recently introduced I/O Braid sensing architecture to enable a series of user studies and experiments which help design suitable interactions and a real-time gesture recognition pipeline. Informed by a gesture elicitation study with 36 participants, we developed a user-dependent classifier for eight discrete gestures with 94% accuracy for 12 participants. In a formal evaluation we show that we can enable precise manipulation with the same architecture. Our quantitative targeting experiment suggests that twisting is faster than existing headphone button controls and is comparable in speed to a capacitive touch surface. Qualitative interview feedback indicates a preference for I/O Braid's interaction over that of in-line headphone controls. Our applications demonstrate how continuous and discrete gestures can be combined to form new, integrated e-textile microinteraction techniques for real-time continuous control, discrete actions and mode switching.
Title: Evaluating the Effect of Timeline Shape on Visualization Task Performance
Authors: family: Di Bartolomeo
given: Sara; family: Pandey
given: Aditeya; family: Leventidis
given: Aristotelis; family: Saffo
given: David; family: Syeda
given: Uzma Haque; family: Carstensdottir
given: Elin; family: Seif El-Nasr
given: Magy; family: Borkin
given: Michelle A.; family: Dunne
given: Cody
Venue: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Abstract: Timelines are commonly represented on a horizontal line, which is not necessarily the most effective way to visualize temporal event sequences. However, few experiments have evaluated how timeline shape influences task performance. We present the design and results of a controlled experiment run on Amazon Mechanical Turk (n=192) in which we evaluate how timeline shape affects task completion time, correctness, and user preference. We tested 12 combinations of 4 shapes --- horizontal line, vertical line, circle, and spiral — and 3 data types — recurrent, non-recurrent, and mixed event sequences. We found good evidence that timeline shape meaningfully affects user task completion time but not correctness and that users have a strong shape preference. Building on our results, we present design guidelines for creating effective timeline visualizations based on user task and data types. A free copy of this paper, the evaluation stimuli and data, and code are available https://osf.io/qr5yu/
Title: OralCam: Enabling Self-Examination and Awareness of Oral Health Using a Smartphone Camera
Authors: family: Liang
given: Yuan; family: Fan
given: Hsuan Wei; family: Fang
given: Zhujun; family: Miao
given: Leiying; family: Li
given: Wen; family: Zhang
given: Xuan; family: Sun
given: Weibin; family: Wang
given: Kun; family: He
given: Lei; family: Chen
given: Xiang 'Anthony'
Venue: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Abstract: Due to a lack of medical resources or oral health awareness, oral diseases are often left unexamined and untreated, affecting a large population worldwide. With the advent of low-cost, sensor-equipped smartphones, mobile apps offer a promising possibility for promoting oral health. However, to the best of our knowledge, no mobile health (mHealth) solutions can directly support a user to self-examine their oral health condition. This paper presents OralCam, the first interactive app that enables end-users' self-examination of five common oral conditions (diseases or early disease signals) by taking smartphone photos of one's oral cavity. OralCam allows a user to annotate additional information (e.g. living habits, pain, and bleeding) to augment the input image, and presents the output hierarchically, probabilistically and with visual explanations to help a laymen user understand examination results. Developed on our in-house dataset that consists of 3,182 oral photos annotated by dental experts, our deep learning based framework achieved an average detection sensitivity of 0.787 over five conditions with high localization accuracy. In a week-long in-the-wild user study (N=18), most participants had no trouble using OralCam and interpreting the examination results. Two expert interviews further validate the feasibility of OralCam for promoting users' awareness of oral health.
Title: Investigating the Opportunities for Technologies to Enhance QoL with Stroke Survivors and their Families
Authors: family: Silva
given: Inês Santos; family: Guerreiro
given: João; family: Rosa
given: Marlene; family: Campos
given: Joana; family: Pascoal
given: Augusto Gil; family: Pinto
given: Sofia; family: Nicolau
given: Hugo
Venue: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Abstract: There are over 80 million stroke survivors globally, making it the main cause of long-term disability worldwide. Not only do the challenges associated with stroke affect the quality of life (QoL) of survivors, but also of their families. To explore these challenges and define design opportunities for technologies to improve the QoL of both stakeholders, we conducted semi-structured interviews with 10 survivors and one of their family members. We uncovered three major interlinked themes: strategies to cope with technological barriers, the (in)adequacy of assistive technologies, and limitations of the rehabilitation process. Findings highlight multiple design opportunities, including the need for meaningful patient-centered tools and methods to improve rehabilitation effectiveness, emotion-aware computing for family emotional support, and re-thinking the nature of assistive technologies to consider the perception of transitory stroke-related disabilities. We thus argue for a new class of dual-purpose technologies that fit survivors' abilities while promoting the regain of function.
Title: User Experiences with Online Status Indicators
Authors: family: Cobb
given: Camille; family: Simko
given: Lucy; family: Kohno
given: Tadayoshi; family: Hiniker
given: Alexis
Venue: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Abstract: Online status indicators (OSIs) improve online communication by helping users convey and assess availability, but they also let users infer potentially sensitive information about one another. We surveyed 200 smartphone users to understand the extent to which users are aware of information shared via OSIs and the extent to which this shapes their behavior. Despite familiarity with OSIs, participants misunderstand many aspects of OSIs, and they describe carefully curating and seeking to control their self-presentation via OSIs. Some users further report leveraging OSI-conveyed information for problematic and malicious purposes. Drawing on existing constructs of app dependence (i.e., when users contort their behavior to meet an app's demands) and app enablement (i.e., when apps enable users to engage in behaviors they feel good about), we demonstrate that current OSI design patterns promote app dependence, and we call for a shift toward OSI designs that are more enabling for users.
Title: Opportunities for Enhancing Access and Efficacy of Peer Sponsorship in Substance Use Disorder Recovery
Authors: family: Heyer
given: Jeremy; family: Schmitt
given: Zachary; family: Dombrowski
given: Lynn; family: Yarosh
given: Svetlana
Venue: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Abstract: Substance use disorders (SUDs) are characterized by an inability to decrease a substance use (e.g., alcohol or opioids) despite negative repercussions. SUDs are clinically diagnosable, hazardous, and considered a public health issue. Sponsorship, a specialized type of peer mentorship, is vital in the recovery process and originates from 12-step fellowship programs such as Alcoholics Anonymous (AA) and Narcotics Anonymous (NA). To investigate sponsorship relationship practices and to identify design opportunities for digitally-mediated peer support, we conducted 27 in-depth interviews with members of AA and NA. We identified five key sponsorship relationship practices relevant for designing social computing tools to support sponsorship and recovery: 1) assessing dyadic compatibility, 2) managing sponsorship with or without technology, 3) establishing boundaries, 4) building a peer support network, and 5) managing anonymity. We identify social computing and digitally-mediated design opportunities and implications.