huashen218/convxai-cia-dataset huggingface dataset:
Title: Social Sensing: Assessing Social Functioning of Patients Living with Schizophrenia using Mobile Phone Sensing
Authors: family: Wang
given: Weichen; family: Mirjafari
given: Shayan; family: Harari
given: Gabriella; family: Ben-Zeev
given: Dror; family: Brian
given: Rachel; family: Choudhury
given: Tanzeem; family: Hauser
given: Marta; family: Kane
given: John; family: Masaba
given: Kizito; family: Nepal
given: Subigya; family: Sano
given: Akane; family: Scherer
given: Emily; family: Tseng
given: Vincent; family: Wang
given: Rui; family: Wen
given: Hongyi; family: Wu
given: Jialing; family: Campbell
given: Andrew
Venue: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Abstract: Impaired social functioning is a symptom of mental illness (e.g., depression, schizophrenia) and a wide range of other conditions (e.g., cognitive decline in the elderly, dementia). Today, assessing social functioning relies on subjective evaluations and self assessments. We propose a different approach and collect detailed social functioning measures and objective mobile sensing data from N=55 outpatients living with schizophrenia to study new methods of passively accessing social functioning. We identify a number of behavioral patterns from sensing data, and discuss important correlations between social function sub-scales and mobile sensing features. We show we can accurately predict the social functioning of outpatients in our study including the following sub-scales: prosocial activities (MAE = 7.79, r = 0.53), which indicates engagement in common social activities; interpersonal behavior (MAE = 3.39, r = 0.57), which represents the number of friends and quality of communications; and employment/occupation (MAE = 2.17, r = 0.62), which relates to engagement in productive employment or a structured program of daily activity. Our work on automatically inferring social functioning opens the way to new forms of assessment and intervention across a number of areas including mental health and aging in place.
Title: Household Surface Interactions: Understanding User Input Preferences and Perceived Home Experiences
Authors: family: Tigwell
given: Garreth W.; family: Crabb
given: Michael
Venue: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Abstract: Households contain a variety of surfaces that are used in a number of activity contexts. As ambient technology becomes commonplace in our homes, it is only a matter of time before these surfaces become linked to computer systems for Household Surface Interaction (HSI). However, little is known about the user experience attached to HSI, and the potential acceptance of HSI within modern homes. To address this problem, we ran a mixed methods user study with 39 participants to examine HSI using nine household surfaces and five common gestures (tap, press, swipe, drag, and pinch). We found that under the right conditions, surfaces with some amount of texture can enhance HSI. Furthermore, perceived good and poor user experience varied among participants for surface type indicating individual preferences. We present findings and design considerations based on surface characteristics and the challenges that users perceive they may have with HSI within their homes.
Title: Engaging Students with Instructor Solutions in Online Programming Homework
Authors: family: Price
given: Thomas W.; family: Williams
given: Joseph Jay; family: Solyst
given: Jaemarie; family: Marwan
given: Samiha
Venue: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Abstract: Students working on programming homework do not receive the same level of support as in the classroom, relying primarily on automated feedback from test cases. One low-effort way to provide more support is by prompting students to compare their solution to an instructor's solution, but it is unclear the best way to design such prompts to support learning. We designed and deployed a randomized controlled trial during online programming homework, where we provided students with an instructor's solution, and randomized whether they were prompted to compare their solution to the instructor's, to fill in the blanks for a written explanation of the instructor's solution, to do both, or neither. Our results suggest that these prompts can effectively engage students in reflecting on instructor solutions, although the results point to design trade-offs between the amount of effort that different prompts require from students and instructors, and their relative impact on learning.
Title: Interspecies Interactions Mediated by Technology: An Avian Case Study at the Zoo
Authors: family: Kleinberger
given: Rébecca; family: Harrington
given: Anne H. K.; family: Yu
given: Lydia; family: van Troyer
given: Akito; family: Su
given: David; family: Baker
given: Janet M.; family: Miller
given: Gabriel
Venue: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Abstract: Enrichment is a methodology for caregivers to offer zoo animals improved psychological and physiological well-being. Although many species rely on auditory senses, sonic enrichment is rarely implemented. Zoo soundscapes are dominated by human-generated noises and do not respond meaningfully to animals' behavior. Designing interactive sonic enrichment systems for animals presents unique ergonomic, ethical, and agency-related challenges. We present a case study of such design. We deployed two novel interventions at the San Diego Zoo to allow Sampson, a music-savvy hyacinth macaw, to gain control over his sonic environment. Our results suggest that (1) the bird uses, understands, and benefits from the system, and (2) visitors play a major role in Sampson's engagement with this technology. With his new agency, the bird seemingly gains more control over his interactions with the public, creating an interspecies experience mediated by technology. The resulting animal-human-computer interaction may inform mediated interspecies experiences in the future.
Title: Technology for Situated and Emergent Play: A Bridging Concept and Design Agenda
Authors: family: Altarriba Bertran
given: Ferran; family: Márquez Segura
given: Elena; family: Isbister
given: Katherine
Venue: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Abstract: Despite the capacity of play to spontaneously emerge in our daily life, the scope of application of play design in HCI is generally narrower, specifically targeting areas of pure leisure, or wholly utilitarian and productive play. Here we focus on the value of play design to respond to and support our natural gravitation towards emergent play that helps to meet our social and emotional needs. We present a bridging concept: Technology for Situated and Emergent Play, i.e. technology design that supports playful engagement that emerges interwoven with our everyday activities outside leisure, and that enriches these activities with socio-emotional value. Our intermediate-level contribution has value as a synthesis piece: it weaves together theories of play and play design and bridges them with concrete design examples. As a bridging concept, it contributes: i) theoretical grounding; ii) inspiring design exemplars that illustrate the theory and foreground its value; and iii) design articulations in the form of valuable experiential qualities and design features. Our work can help to focus design agendas for playful technology and inspire future designs in this space.
Title: An Experimental Study of Bias in Platform Worker Ratings: The Role of Performance Quality and Gender
Authors: family: Jahanbakhsh
given: Farnaz; family: Cranshaw
given: Justin; family: Counts
given: Scott; family: Lasecki
given: Walter S.; family: Inkpen
given: Kori
Venue: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Abstract: We study how the ratings people receive on online labor platforms are influenced by their performance, gender, their rater's gender, and displayed ratings from other raters. We conducted a deception study in which participants collaborated on a task with a pair of simulated workers, who varied in gender and performance level, and then rated their performance. When the performance of paired workers was similar, low-performing females were rated lower than their male counterparts. Where there was a clear performance difference between paired workers, low-performing females were preferred over a similarly-performing male peer. Furthermore, displaying an average rating from other raters made ratings more extreme, resulting in high performing workers receiving significantly higher ratings and low performers lower ratings compared to when average ratings were absent. This work contributes an empirical understanding of when biases in ratings manifest, and offers recommendations for how online work platforms can counter these biases.
Title: Comparing Smartphone Speech Recognition and Touchscreen Typing for Composition and Transcription
Authors: family: Foley
given: Margaret; family: Casiez
given: Géry; family: Vogel
given: Daniel
Venue: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Abstract: Ruan et al. found transcribing short phrases with speech recognition nearly 200% faster than typing on a smartphone. We extend this comparison to a novel composition task, using a protocol that enables a controlled comparison with transcription. Results show that both composing and transcribing with speech is faster than typing. But, the magnitude of this difference is lower with composition, and speech has a lower error rate than keyboard during composition, but not during transcription. When transcribing, speech outperformed typing in most NASA-TLX measures, but when composing, there were no significant differences between typing and speech for any measure except physical demand.
Title: Understanding the Use of Crisis Informatics Technology among Older Adults
Authors: family: Zhang
given: Yixuan; family: Suhaimi
given: Nurul; family: Azghandi
given: Rana; family: Joseph
given: Mary Amulya; family: Kim
given: Miso; family: Griffin
given: Jacqueline; family: Parker
given: Andrea G.
Venue: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Abstract: Mass emergencies increasingly pose significant threats to human life, with a disproportionate burden being incurred by older adults. Research has explored how mobile technology can mitigate the effects of mass emergencies. However, less work has examined how mobile technologies support older adults during emergencies, considering their unique needs. To address this research gap, we interviewed 16 older adults who had recent experience with an emergency evacuation to understand the perceived value of using mobile technology during emergencies. We found that there was a lack of awareness and engagement with existing crisis apps. Our findings characterize the ways in which our participants did and did not feel crisis informatics tools address human values, including basic needs and esteem needs. We contribute an understanding of how older adults used mobile technology during emergencies and their perspectives on how well such tools address human values.
Title: Voice+Tactile: Augmenting In-vehicle Voice User Interface with Tactile Touchpad Interaction
Authors: family: Jung
given: Jingun; family: Lee
given: Sangyoon; family: Hong
given: Jiwoo; family: Youn
given: Eunhye; family: Lee
given: Geehyuk
Venue: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Abstract: Promisingly, driving is adapting to a Voice User Interface (VUI) that lets drivers utilize diverse applications with little effort. However, the VUI has innate usability issues, such as a turn-taking problem, a short-term memory workload, inefficient controls, and difficulty correcting errors. To overcome these weaknesses, we explored supplementing the VUI with tactile interaction. As an early result, we present the Voice+Tactile interactions that augment the VUI via multi-touch inputs and high-resolution tactile outputs. We designed various Voice+Tactile interactions to support different VUI interaction stages and derived four Voice+Tactile interaction themes: Status Feedback, Input Adjustment, Output Control, and Finger Feedforward. A user study showed that the Voice+Tactile interactions improved the VUI efficiency and its user experiences without incurring significant additional distraction overhead on driving. We hope these early results open new research questions to improve in-vehicle VUI with a tactile channel.
Title: Let's Draw: Detecting and Measuring Parkinson's Disease on Smartphones
Authors: family: Kuosmanen
given: Elina; family: Kan
given: Valerii; family: Visuri
given: Aku; family: Hosio
given: Simo; family: Ferreira
given: Denzil
Venue: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Abstract: Spiral drawing has been utilized for years as a clinical tool to observe tremors and other abnormal movements in the assessment of different movement disorders. Specifically, in Parkinson's Disease (PD), patients' motor functionalities are measured by various tests, and spiral drawing is one of the proven techniques for assessing the severity of PD motor symptoms. Traditionally, this test is performed on pen and paper, and visually assessed by a clinician. There have been successful efforts for digitizing this test on tablets. Here, we describe a smartphone-based digitized version of the spiral drawing test. Moreover, we introduce a square-shaped drawing to solve an identified challenge of a smaller screen estate: finger occlusion while drawing. Both approaches are evaluated with 8 Parkinson's Disease patients and 6 age-matching control participants. Based on earlier studies and our data, we select suitable motion parameters for quantifying the task. Our results show an observable, statistically difference in performance between users with Parkinson's Disease and the control group in drawing accuracy.
Title: Gaiters: Exploring Skin Stretch Feedback on Legs for Enhancing Virtual Reality Experiences
Authors: family: Wang
given: Chi; family: Huang
given: Da-Yuan; family: Hsu
given: Shuo-Wen; family: Lin
given: Cheng-Lung; family: Chiu
given: Yeu-Luen; family: Hou
given: Chu-En; family: Chen
given: Bing-Yu
Venue: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Abstract: We propose generating two-dimensional skin stretch feedback on the user's legs. Skin stretch is useful cutaneous feedback to induce the perception of virtual textures and illusory forces and to deliver directional cues. This feedback has been applied to the head, body, and upper limbs to simulate rich physical properties in virtual reality (VR). However, how to expand the benefit of skin stretch feedback and apply it to the lower limbs, remains to be explored. Our first two psychophysical studies examined the minimum changes in skin stretch distance and stretch angle that are perceivable by participants. We then designed and implemented Gaiters, a pair of ungrounded, leg-worn devices, each of which is able to generate multiple two-dimensional skin stretches on the skin of the user's leg. With Gaiters, we conducted an exploratory study to understand participants' experiences when coupling skin stretch patterns with various lower limb actions. The results indicate that rich haptic experiences can be created by our prototype. Finally, a user evaluation indicates that participants enjoyed the experiences when using Gaiters and considered skin stretch as compelling haptic feedback on the legs.
Title: DFSeer: A Visual Analytics Approach to Facilitate Model Selection for Demand Forecasting
Authors: family: Sun
given: Dong; family: Feng
given: Zezheng; family: Chen
given: Yuanzhe; family: Wang
given: Yong; family: Zeng
given: Jia; family: Yuan
given: Mingxuan; family: Pong
given: Ting-Chuen; family: Qu
given: Huamin
Venue: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Abstract: Selecting an appropriate model to forecast product demand is critical to the manufacturing industry. However, due to the data complexity, market uncertainty and users' demanding requirements for the model, it is challenging for demand analysts to select a proper model. Although existing model selection methods can reduce the manual burden to some extent, they often fail to present model performance details on individual products and reveal the potential risk of the selected model. This paper presents DFSeer, an interactive visualization system to conduct reliable model selection for demand forecasting based on the products with similar historical demand. It supports model comparison and selection with different levels of details. Besides, it shows the difference in model performance on similar products to reveal the risk of model selection and increase users' confidence in choosing a forecasting model. Two case studies and interviews with domain experts demonstrate the effectiveness and usability of DFSeer.
Title: Relational Aspects in Patient-provider Interactions: A Facial Paralysis Case Study
Authors: family: Zhu
given: Haining; family: Moffa
given: Zachary J.; family: Carroll
given: John M.
Venue: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Abstract: Facial appearance is significant for everyday interactions, but hundreds of thousands of people have interactions negatively affected by facial paralysis (FP) annually. FP treatment utilizes multiple components and requires significant collaboration amongst multidisciplinary specialists and patients. Complex interactions in these contexts offer ample challenges for designers to technologically support healthcare providers in their processes. We conduct a formative case study, employing 20 clinic observations and 11 interviews, to investigate FP treatment workflow. We use cognitive authority theory (CAT) to understand relational factors in patient-provider collaboration. We then pinpoint structural and relational components of workflow challenges and discuss the utility of these distinctions; notably, we identify that patient adherence lapses caused by perceived plateaus may be primarily relational and caused by unmet expectations. Our work adds to patient-provider interaction literature and sheds light upon technology design for healthcare team contexts with significant patient obligations.
Title: HeadReach: Using Head Tracking to Increase Reachability on Mobile Touch Devices
Authors: family: Voelker
given: Simon; family: Hueber
given: Sebastian; family: Corsten
given: Christian; family: Remy
given: Christian
Venue: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Abstract: People often operate their smartphones with only one hand, using just their thumb for touch input. With today's larger smartphones, this leads to a reachability issue: Users can no longer comfortably touch everywhere on the screen without changing their grip. We investigate using the head tracking in modern smartphones to address this reachability issue. We developed three interaction techniques, pure head (PH), head + touch (HT), and head area + touch (HA), to select targets beyond the reach of one's thumb. In two user studies, we found that selecting targets using HT and HA had higher success rates than the default direct touch (DT) while standing (by about 9%) and walking (by about 12%), while being moderately slower. HT and HA were also faster than one of the best techniques, BezelCursor (BC) (by about 20% while standing and 6% while walking), while having the same success rate.
Title: FitByte: Automatic Diet Monitoring in Unconstrained Situations Using Multimodal Sensing on Eyeglasses
Authors: family: Bedri
given: Abdelkareem; family: Li
given: Diana; family: Khurana
given: Rushil; family: Bhuwalka
given: Kunal; family: Goel
given: Mayank
Venue: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Abstract: In an attempt to help users reach their health goals and practitioners understand the relationship between diet and disease, researchers have proposed many wearable systems to automatically monitor food consumption. When a person consumes food, he/she brings the food close to their mouth, take a sip or bite and chew, and then swallow. Most diet monitoring approaches focus on one of these aspects of food intake, but this narrow reliance requires high precision and often fails in noisy and unconstrained situations common in a person's daily life. In this paper, we introduce FitByte, a multi-modal sensing approach on a pair of eyeglasses that tracks all phases of food intake. FitByte contains a set of inertial and optical sensors that allow it to reliably detect food intake events in noisy environments. It also has an on-board camera that opportunistically captures visuals of the food as the user consumes it. We evaluated the system in two studies with decreasing environmental constraints with 23 participants. On average, FitByte achieved 89% F1-score in detecting eating and drinking episodes.
Title: Modeling Human Visual Search Performance on Realistic Webpages Using Analytical and Deep Learning Methods
Authors: family: Yuan
given: Arianna; family: Li
given: Yang
Venue: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Abstract: Modeling visual search not only offers an opportunity to predict the usability of an interface before actually testing it on real users but also advances scientific understanding about human behavior. In this work, we first conduct a set of analyses on a large-scale dataset of visual search tasks on realistic webpages. We then present a deep neural network that learns to predict the scannability of webpage content, i.e., how easy it is for a user to find a specific target. Our model leverages both heuristic-based features such as target size and unstructured features such as raw image pixels. This approach allows us to model complex interactions that might be involved in a realistic visual search task, which can not be achieved by traditional analytical models. We analyze the model behavior to offer our insights into how the salience map learned by the model aligns with human intuition.
Title: Future Opportunities for IoT to Support People with Parkinson's
Authors: family: McNaney
given: Roisin; family: Tsekleves
given: Emmanuel; family: Synnott
given: Jonathan
Venue: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Abstract: Recent years have seen an explosion of internet of things (IoT) technologies being released to the market. There has also been an emerging interest in the potentials of IoT devices to support people with chronic health conditions. In this paper, we describe the results of engagements to scope the future potentials of IoT for supporting people with Parkinson's (PwP). We ran a 2-day multi-disciplinary event with professionals with expertise in Parkinson's and IoT, to explore the opportunities, challenges and benefits. We then ran 4 workshops, engaging 13 PwP and caregivers, to scope out the needs, values and desires that the community has for utilizing IoT to monitor their symptoms. This work contributes considerations for future IoT solutions that might support PwP in better understanding their condition, through the provision of objective measurements that correspond to their, currently unmeasured, subjective experiences.