huashen218/convxai-cia-dataset huggingface dataset:
Title: Selection-based Text Entry in Virtual Reality
Authors: family: Speicher
given: Marco; family: Feit
given: Anna Maria; family: Ziegler
given: Pascal; family: Krüger
given: Antonio
Venue: Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems
Keywords: virtual reality, mid-air, pointing, user experience, text entry, task performance

Abstract: In recent years, Virtual Reality (VR) and 3D User Interfaces (3DUI) have seen a drastic increase in popularity, especially in terms of consumer-ready hardware and software. While the technology for input as well as output devices is market ready, only a few solutions for text input exist, and empirical knowledge about performance and user preferences is lacking. In this paper, we study text entry in VR by selecting characters on a virtual keyboard. We discuss the design space for assessing selection-based text entry in VR. Then, we implement six methods that span different parts of the design space and evaluate their performance and user preferences. Our results show that pointing using tracked hand-held controllers outperforms all other methods. Other methods such as head pointing can be viable alternatives depending on available resources. We summarize our findings by formulating guidelines for choosing optimal virtual keyboard text entry methods in VR.
Title: Effects of Viewing Multiple Viewpoint Videos on Metacognition of Collaborative Experiences
Authors: family: Sumi
given: Yasuyuki; family: Suwa
given: Masaki; family: Hanaue
given: Koichi
Venue: Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems
Keywords: experience capturing, metacognition, multiple viewpoint videos

Abstract: This paper discusses the effects of multiple viewpoint videos for metacognition of experiences. We present a system for recording multiple users' collaborative experiences by wearable and environmental sensors, and another system for viewing multiple viewpoint videos automatically identified and extracted to associate to individual users. We designed an experiment to compare the metacognition of one's own experience between those based on memory and those supported by video viewing. The experimental results show that metacognitive descriptions related to one's own mind, such as feelings and preferences, are possible regardless whether a person is viewing videos, but such episodic descriptions as the content of someone's utterance and what s/he felt associated with it are strongly promoted by video viewing. We conducted another experiment where the same participants did identical metacognitive description tasks about half a year after the previous experiment. Through the experiments, we found the first-person view video is mostly used for confirming the episodic facts immediately after the experience, whereas after half a year, even one's own experience is often felt like the experiences of others therefore the videos capturing themselves from the conversation partners and environment become important for thinking back to the situations where they were placed.
Title: I Lead, You Help but Only with Enough Details: Understanding User Experience of Co-Creation with Artificial Intelligence
Authors: family: Oh
given: Changhoon; family: Song
given: Jungwoo; family: Choi
given: Jinhan; family: Kim
given: Seonghyeon; family: Lee
given: Sungwoo; family: Suh
given: Bongwon
Venue: Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems
Keywords: human-ai interaction, artificial intelligence, human computer collaboration

Abstract: Recent advances in artificial intelligence (AI) have increased the opportunities for users to interact with the technology. Now, users can even collaborate with AI in creative activities such as art. To understand the user experience in this new user--AI collaboration, we designed a prototype, DuetDraw, an AI interface that allows users and the AI agent to draw pictures collaboratively. We conducted a user study employing both quantitative and qualitative methods. Thirty participants performed a series of drawing tasks with the think-aloud method, followed by post-hoc surveys and interviews. Our findings are as follows: (1) Users were significantly more content with DuetDraw when the tool gave detailed instructions. (2) While users always wanted to lead the task, they also wanted the AI to explain its intentions but only when the users wanted it to do so. (3) Although users rated the AI relatively low in predictability, controllability, and comprehensibility, they enjoyed their interactions with it during the task. Based on these findings, we discuss implications for user interfaces where users can collaborate with AI in creative works.
Title: Supporting Collaborative Health Tracking in the Hospital: Patients' Perspectives
Authors: family: Mishra
given: Sonali R.; family: Miller
given: Andrew D.; family: Haldar
given: Shefali; family: Khelifi
given: Maher; family: Eschler
given: Jordan; family: Elera
given: Rashmi G.; family: Pollack
given: Ari H.; family: Pratt
given: Wanda
Venue: Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems
Keywords: hospital, health informatics, self-tracking, patient-clinician collaboration, personal informatics, patient safety, patient engagement

Abstract: The hospital setting creates a high-stakes environment where patients' lives depend on accurate tracking of health data. Despite recent work emphasizing the importance of patients' engagement in their own health care, less is known about how patients track their health and care in the hospital. Through interviews and design probes, we investigated hospitalized patients' tracking activity and analyzed our results using the stage-based personal informatics model. We used this model to understand how to support the tracking needs of hospitalized patients at each stage. In this paper, we discuss hospitalized patients' needs for collaboratively tracking their health with their care team. We suggest future extensions of the stage-based model to accommodate collaborative tracking situations, such as hospitals, where data is collected, analyzed, and acted on by multiple people. Our findings uncover new directions for HCI research and highlight ways to support patients in tracking their care and improving patient safety.
Title: Investigating the Impact of Gender on Rank in Resume Search Engines
Authors: family: Chen
given: Le; family: Ma
given: Ruijun; family: Hannák
given: Anikó; family: Wilson
given: Christo
Venue: Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems
Keywords: information retrieval, discrimination, algorithm auditing

Abstract: In this work we investigate gender-based inequalities in the context of resume search engines, which are tools that allow recruiters to proactively search for candidates based on keywords and filters. If these ranking algorithms take demographic features into account (directly or indirectly), they may produce rankings that disadvantage some candidates. We collect search results from Indeed, Monster, and CareerBuilder based on 35 job titles in 20 U. S. cities, resulting in data on 855K job candidates. Using statistical tests, we examine whether these search engines produce rankings that exhibit two types of indirect discrimination: individual and group unfairness. Furthermore, we use controlled experiments to show that these websites do not use inferred gender of candidates as explicit features in their ranking algorithms.
Title: The Effect of Offset Correction and Cursor on Mid-Air Pointing in Real and Virtual Environments
Authors: family: Mayer
given: Sven; family: Schwind
given: Valentin; family: Schweigert
given: Robin; family: Henze
given: Niels
Venue: Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems
Keywords: offset correction, virtual environment, ray casting, cursor, modeling, mid-air pointing

Abstract: Pointing at remote objects to direct others' attention is a fundamental human ability. Previous work explored methods for remote pointing to select targets. Absolute pointing techniques that cast a ray from the user to a target are affected by humans' limited pointing accuracy. Recent work suggests that accuracy can be improved by compensating systematic offsets between targets a user aims at and rays cast from the user to the target. In this paper, we investigate mid-air pointing in the real world and virtual reality. Through a pointing study, we model the offsets to improve pointing accuracy and show that being in a virtual environment affects how users point at targets. In the second study, we validate the developed model and analyze the effect of compensating systematic offsets. We show that the provided model can significantly improve pointing accuracy when no cursor is provided. We further show that a cursor improves pointing accuracy but also increases the selection time.
Title: CLAW: A Multifunctional Handheld Haptic Controller for Grasping, Touching, and Triggering in Virtual Reality
Authors: family: Choi
given: Inrak; family: Ofek
given: Eyal; family: Benko
given: Hrvoje; family: Sinclair
given: Mike; family: Holz
given: Christian
Venue: Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems
Keywords: texture, force feedback, haptics, trigger, controller design, grasping, touching, virtual reality

Abstract: CLAW is a handheld virtual reality controller that augments the typical controller functionality with force feedback and actuated movement to the index finger. Our controller enables three distinct interactions (grasping virtual object, touching virtual surfaces, and triggering) and changes its corresponding haptic rendering by sensing the differences in the user's grasp. A servo motor coupled with a force sensor renders controllable forces to the index finger during grasping and touching. Using position tracking, a voice coil actuator at the index fingertip generates vibrations for various textures synchronized with finger movement. CLAW also supports a haptic force feedback in the trigger mode when the user holds a gun. We describe the design considerations for CLAW and evaluate its performance through two user studies. The first study obtained qualitative user feedback on the naturalness, effectiveness, and comfort when using the device. The second study investigated the ease of the transition between grasping and touching when using our device.
Title: Ripple Thermostat: Affecting the Emotional Experience through Interactive Force Feedback and Shape Change
Authors: family: van Oosterhout
given: Anke; family: Bruns Alonso
given: Miguel; family: Jumisko-Pyykkö
given: Satu
Venue: Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems
Keywords: shape-changing interfaces, actuated interfaces, haptic force feedback, affective computing

Abstract: Force feedback and shape change are modalities with a growing application potential beyond the more traditional GUIs. We present two studies that explored the effect of these modalities on the emotional experience when interacting with an intelligent thermostat. The first study compared visual feedback, force feedback, and a combination of force feedback and shape change. Results indicate that force feedback correlates to experienced dominance during interaction, while shape change mainly affects experienced arousal. The second study explored how force feedback and shape change could communicate affective meaning during interaction with the thermostat through a co-design study. Participants designed the thermostat behavior for three scenarios supporting energy savings. Results suggest that despite their abstractness, force feedback and shape change convey affective meaning during the user-system dialogue. The findings contribute to the design of intelligible and intuitive feedback.
Title: A Qualitative Exploration of Perceptions of Algorithmic Fairness
Authors: family: Woodruff
given: Allison; family: Fox
given: Sarah E.; family: Rousso-Schindler
given: Steven; family: Warshaw
given: Jeffrey
Venue: Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems
Keywords: algorithmic fairness, algorithmic discrimination

Abstract: Algorithmic systems increasingly shape information people are exposed to as well as influence decisions about employment, finances, and other opportunities. In some cases, algorithmic systems may be more or less favorable to certain groups or individuals, sparking substantial discussion of algorithmic fairness in public policy circles, academia, and the press. We broaden this discussion by exploring how members of potentially affected communities feel about algorithmic fairness. We conducted workshops and interviews with 44 participants from several populations traditionally marginalized by categories of race or class in the United States. While the concept of algorithmic fairness was largely unfamiliar, learning about algorithmic (un)fairness elicited negative feelings that connect to current national discussions about racial injustice and economic inequality. In addition to their concerns about potential harms to themselves and society, participants also indicated that algorithmic fairness (or lack thereof) could substantially affect their trust in a company or product.
Title: The Benefits and Challenges of Video Calling for Emergency Situations
Authors: family: Neustaedter
given: Carman; family: Jones
given: Brennan; family: O'Hara
given: Kenton; family: Sellen
given: Abigail
Venue: Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems
Keywords: mobile video calling, situation awareness, dispatchers, emergency calling, call takers, collaboration

Abstract: In the coming years, emergency calling services in North America will begin to incorporate new modalities for reporting emergencies, including video-based calling. The challenge is that we know little of how video calling systems should be designed and what benefits or challenges video calling might bring. We conducted observations and contextual interviews within three emergency response call centres to investigate these points. We focused on the work practices of call takers and dispatchers. Results show that video calls could provide valuable contextual information about a situation and help to overcome call taker challenges with information ambiguity, location, deceit, and communication issues. Yet video calls have the potential to introduce issues around control, information overload, and privacy if systems are not designed well. These results point to the need to think about emergency video calling along a continuum of visual modalities ranging from audio calls accompanied with images or video clips to one-way video streams to two-way video streams where camera control and camera work need to be carefully designed.
Title: Whiskers: Exploring the Use of Ultrasonic Haptic Cues on the Face
Authors: family: Gil
given: Hyunjae; family: Son
given: Hyungki; family: Kim
given: Jin Ryong; family: Oakley
given: Ian
Venue: Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems
Keywords: notifications, face, smartglasses, haptic, tactile

Abstract: Haptic cues are a valuable feedback mechanism for smart glasses. Prior work has shown how they can support navigation, deliver notifications and cue targets. However, a focus on actuation technologies such as mechanical tactors or fans has restricted the scope of research to a small number of cues presented at fixed locations. To move beyond this limitation, we explore perception of in-air ultrasonic haptic cues on the face. We present two studies examining the fundamental properties of localization, duration and movement perception on three facial sites suitable for use with glasses: the cheek, the center of the forehead, and above the eyebrow. The center of the forehead led to optimal performance with a localization error of 3.77mm and accurate duration (80%) and movement perception (87%). We apply these findings in a study delivering eight different ultrasonic notifications and report mean recognition rates of up to 92.4% (peak: 98.6%). We close with design recommendations for ultrasonic haptic cues on the face.
Title: Let's Play! Digital and Analog Play between Preschoolers and Parents
Authors: family: Hiniker
given: Alexis; family: Lee
given: Bongshin; family: Kientz
given: Julie A.; family: Radesky
given: Jenny S.
Venue: Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems
Keywords: parent-child interaction, child-computer interaction, parents, children, play, joint media engagement

Abstract: Play is an enjoyable and developmentally useful part of early childhood, and parent-child play is a highly productive mechanism by which children learn to participate in the world. We conducted an observational lab study to examine how 15 parent-child pairs (children age 4-6) respond to and play with tablet apps as compared to analog toys. We found that parents and children were less likely to engage with each other or to respond to each other's bids for attention during play sessions with tab-lets versus play sessions with toys. We also observed that specific design features of tablet devices and children's apps-such as one-sided interfaces, game paradigms that demand continual attention, and lack of support for parallel interaction-are the primary mechanism shaping these differences. We provide guidance suggesting how children's apps might be re-designed to preserve the ad-vantages of digital play experiences while also evolving to build in the advantages of traditional toys.
Title: Combating Attrition in Digital Self-Improvement Programs using Avatar Customization
Authors: family: Birk
given: Max V.; family: Mandryk
given: Regan L.
Venue: Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems
Keywords: volitional engagement, customization, avatars, motivation, behaviour change, self-improvement programs

Abstract: Digital self-improvement programs (e.g., interventions, training programs, self-help apps) are widely accessible, but can not employ the same degree of external regulation as programs delivered in controlled environments. As a result, they suffer from high attrition -- even the best programs won't work if people don't use them. We propose that volitional engagement -- facilitated through avatar customization -- can help combat attrition. We asked 250 participants to engage daily for 3 weeks in a one-minute breathing exercise for anxiety reduction, using either a generic avatar or one that they customized. Customizing an avatar resulted in significantly less attrition and more sustained engagement as measured through login counts. The problem of attrition affects self-improvement programs across a range of do-mains; we provide a subtle, versatile, and broadly-applicable solution.
Title: Use the Force Picker, Luke: Space-Efficient Value Input on Force-Sensitive Mobile Touchscreens
Authors: family: Corsten
given: Christian; family: Voelker
given: Simon; family: Link
given: Andreas; family: Borchers
given: Jan
Venue: Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems
Keywords: value input, force, bidirectional, pressure, rate-based control

Abstract: Picking values from long ordered lists, such as when setting a date or time, is a common task on smartphones. However, the system pickers and tables used for this require significant screen space for spinning and dragging, covering other information or pushing it off-screen. The Force Picker reduces this footprint by letting users increase and decrease values over a wide range using force touch for rate-based control. However, changing input direction this way is difficult. We propose three techniques to address this. With our best candidate, Thumb-Roll, the Force Picker lets untrained users achieve similar accuracy as a standard picker, albeit less quickly. Shrinking it to a single table row, 20% of the iOS picker height, slightly affects completion time, but not accuracy. Intriguingly, after 70 minutes of training, users were significantly faster with this minimized Thumb-Roll Picker compared to the standard picker, at the same accuracy and only 6% of the gesture footprint. We close with application examples.
Title: Live Sketch: Video-driven Dynamic Deformation of Static Drawings
Authors: family: Su
given: Qingkun; family: Bai
given: Xue; family: Fu
given: Hongbo; family: Tai
given: Chiew-Lan; family: Wang
given: Jue
Venue: Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems
Keywords: motion transfer, dynamic deformation, motion extraction, video examples, sketch animation

Abstract: Creating sketch animations using traditional tools requires special artistic skills, and is tedious even for trained professionals. To lower the barrier for creating sketch animations, we propose a new system, emphLive Sketch,&lt;/i&gt; which allows novice users to interactively bring static drawings to life by applying deformation-based animation effects that are extracted from video examples. Dynamic deformation is first extracted as a sparse set of moving control points from videos and then transferred to a static drawing. Our system addresses a few major technical challenges, such as motion extraction from video, video-to-sketch alignment, and many-to-one motion-driven sketch animation. While each of the sub-problems could be difficult to solve fully automatically, we present reliable solutions by combining new computational algorithms with intuitive user interactions. Our pilot study shows that our system allows both users with or without animation skills to easily add dynamic deformation to static drawings.
Title: ECGLens: Interactive Visual Exploration of Large Scale ECG Data for Arrhythmia Detection
Authors: family: Xu
given: Ke; family: Guo
given: Shunan; family: Cao
given: Nan; family: Gotz
given: David; family: Xu
given: Aiwen; family: Qu
given: Huamin; family: Yao
given: Zhenjie; family: Chen
given: Yixin
Venue: Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems
Keywords: visualization, interaction design, visual design, artifact or system, health - clinical

Abstract: The Electrocardiogram (ECG) is commonly used to detect arrhythmias. Traditionally, a single ECG observation is used for diagnosis, making it difficult to detect irregular arrhythmias. Recent technology developments, however, have made it cost-effective to collect large amounts of raw ECG data over time. This promises to improve diagnosis accuracy, but the large data volume presents new challenges for cardiologists. This paper introduces ECGLens, an interactive system for arrhythmia detection and analysis using large-scale ECG data. Our system integrates an automatic heartbeat classification algorithm based on convolutional neural network, an outlier detection algorithm, and a set of rich interaction techniques. We also introduce A-glyph, a novel glyph designed to improve the readability and comparison of ECG signals. We report results from a comprehensive user study showing that A-glyph improves the efficiency in arrhythmia detection, and demonstrate the effectiveness of ECGLens in arrhythmia detection through two expert interviews.