huashen218/convxai-cia-dataset huggingface dataset:
Title: An Evaluation of Touch Input at the Edge of a Table
Authors: family: Joshi
given: Nikhita; family: Vogel
given: Daniel
Venue: Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems
Keywords: fitts' law, controlled experiments, interaction techniques

Abstract: Tables, desks, and counters are often nearby, motivating their use as interactive surfaces. However, they are typically cluttered. As an alternative, we explore touch input along the 'edge' of table-like surfaces. The performance of tapping, crossing, and dragging is tested along the two ridges and front face of a table edge. Results show top ridge movement time is comparable to the top face when tapping or dragging. When crossing, both ridges are at least 11% faster than the top face. Effective width analysis is used to model performance and provide recommended target sizes. Based on observed user behaviour, variations of top and bottom ridge crossing are explored in a second study, and design recommendations with example applications are provided.
Title: Pay Attention, Please: Formal Language Improves Attention in Volunteer and Paid Online Experiments
Authors: family: August
given: Tal; family: Reinecke
given: Katharina
Venue: Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems
Keywords: online experiments, data quality, attention, participant engagement, language formality

Abstract: Participant engagement in online studies is key to collecting reliable data, yet achieving it remains an often discussed challenge in the research community. One factor that might impact engagement is the formality of language used to communicate with participants throughout the study. Prior work has found that language formality can convey social cues and power hierarchies, affecting people's responses and actions. We explore how formality influences engagement, measured by attention, dropout, time spent on the study and participant performance, in an online study with 369 participants on Mechanical Turk (paid) and LabintheWild (volunteer). Formal language improves participant attention compared to using casual language in both paid and volunteer conditions, but does not affect dropout, time spent, or participant performance. We suggest using more formal language in studies containing complex tasks where fully reading instructions is especially important. We also highlight trade-offs that different recruitment incentives provide in online experimentation.
Title: Enhancing Texture Perception in Virtual Reality Using 3D-Printed Hair Structures
Authors: family: Degraen
given: Donald; family: Zenner
given: André; family: Krüger
given: Antonio
Venue: Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems
Keywords: 3d printing, passive haptic feedback, texture perception

Abstract: Experiencing materials in virtual reality (VR) is enhanced by combining visual and haptic feedback. While VR easily allows changes to visual appearances, modifying haptic impressions remains challenging. Existing passive haptic techniques require access to a large set of tangible proxies. To reduce the number of physical representations, we look towards fabrication to create more versatile counterparts. In a user study, 3D-printed hairs with length varying in steps of 2.5 mm were used to influence the feeling of roughness and hardness. By overlaying fabricated hair with visual textures, the resolution of the user's haptic perception increased. As changing haptic sensations are able to elicit perceptual switches, our approach can extend a limited set of textures to a much broader set of material impressions. Our results give insights into the effectiveness of 3D-printed hair for enhancing texture perception in VR.
Title: The Design of Social Drones: A Review of Studies on Autonomous Flyers in Inhabited Environments
Authors: family: Baytas
given: Mehmet Aydin; family: Çay
given: Damla; family: Zhang
given: Yuchong; family: Obaid
given: Mohammad; family: Yantaç
given: Asim Evren; family: Fjeld
given: Morten
Venue: Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems
Keywords: autonomous agents, design knowledge, human-drone interaction, drone design, social drones, drones, user studies, empirical studies

Abstract: The design space of social drones, where autonomous flyers operate in close proximity to human users or bystanders, is distinct from use cases involving a remote human operator and/or an uninhabited environment; and warrants foregrounding human-centered design concerns. Recently, research on social drones has followed a trend of rapid growth. This paper consolidates the current state of the art in human-centered design knowledge about social drones through a review of relevant studies, scaffolded by a descriptive framework of design knowledge creation. Our analysis identified three high-level themes that sketch out knowledge clusters in the literature, and twelve design concerns which unpack how various dimensions of drone aesthetics and behavior relate to pertinent human responses. These results have the potential to inform and expedite future research and practice, by supporting readers in defining and situating their future contributions. The materials and results of our analysis are also published in an open online repository that intends to serve as a living hub for a community of researchers and designers working with social drones.
Title: Recipes for Programmable Money
Authors: family: Elsden
given: Chris; family: Feltwell
given: Tom; family: Lawson
given: Shaun; family: Vines
given: John
Venue: Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems
Keywords: automation, ifttt, money, fintech

Abstract: This paper presents a qualitative study of the recent integration of a UK-based, digital-first mobile banking app - Monzo - with the web automation service IFTTT (If This Then That). Through analysis of 113 unique IFTTT 'recipes' shared by Monzo users on public community forums, we illustrate the potentially diverse functions of these recipes, and how they are achieved through different kinds of automation. Beyond achieving more convenient and efficient financial management, we note many playful and expressive applications of conditionality and automation that far extend traditional functions of banking applications and infrastructure. We use these findings to map opportunities, challenges and areas of future research in the development of 'programmable money' and related financial technologies. Specifically, we present design implications for the extension of native digital banking applications; novel uses of banking data; the applicability of blockchains and smart contracts; and future forms of financial autonomy.
Title: Crowdsourcing Interface Feature Design with Bayesian Optimization
Authors: family: Dudley
given: John J.; family: Jacques
given: Jason T.; family: Kristensson
given: Per Ola
Venue: Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems
Keywords: crowdsourcing, interface design, optimization

Abstract: Designing novel interfaces is challenging. Designers typically rely on experience or subjective judgment in the absence of analytical or objective means for selecting interface parameters. We demonstrate Bayesian optimization as an efficient tool for objective interface feature refinement. Specifically, we show that crowdsourcing paired with Bayesian optimization can rapidly and effectively assist interface design across diverse deployment environments. Experiment 1 evaluates the approach on a familiar 2D interface design problem: a map search and review use case. Adding a degree of complexity, Experiment 2 extends Experiment 1 by switching the deployment environment to mobile-based virtual reality. The approach is then demonstrated as a case study for a fundamentally new and unfamiliar interaction design problem: web-based augmented reality. Finally, we show how the model generated as an outcome of the refinement process can be used for user simulation and queried to deliver various design insights.
Title: Comparing Effectiveness and Engagement of Data Comics and Infographics
Authors: family: Wang
given: Zezhong; family: Wang
given: Shunming; family: Farinella
given: Matteo; family: Murray-Rust
given: Dave; family: Henry Riche
given: Nathalie; family: Bach
given: Benjamin
Venue: Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems
Keywords: visualization, engagement, effectiveness, comics

Abstract: This paper compares the effectiveness of data comics and infographics for data-driven storytelling. While infographics are widely used, comics are increasingly popular for explaining complex and scientific concepts. However, empirical evidence comparing the effectiveness and engagement of infographics, comics and illustrated texts is still lacking. We report on the results of two complementary studies, one in a controlled setting and one in the wild. Our results suggest participants largely prefer data comics in terms of enjoyment, focus, and overall engagement and that comics improve understanding and recall of information in the stories. Our findings help to understand the respective roles of the investigated formats as well as inform the design of more effective data comics and infographics.
Title: Resilient Chatbots: Repair Strategy Preferences for Conversational Breakdowns
Authors: family: Ashktorab
given: Zahra; family: Jain
given: Mohit; family: Liao
given: Q. Vera; family: Weisz
given: Justin D.
Venue: Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems
Keywords: conversational breakdown, conversational agents, chatbots, repair, grounding

Abstract: Text-based conversational systems, also referred to as chatbots, have grown widely popular. Current natural language understanding technologies are not yet ready to tackle the complexities in conversational interactions. Breakdowns are common, leading to negative user experiences. Guided by communication theories, we explore user preferences for eight repair strategies, including ones that are common in commercially-deployed chatbots (e.g., confirmation, providing options), as well as novel strategies that explain characteristics of the underlying machine learning algorithms. We conducted a scenario-based study to compare repair strategies with Mechanical Turk workers (N=203). We found that providing options and explanations were generally favored, as they manifest initiative from the chatbot and are actionable to recover from breakdowns. Through detailed analysis of participants' responses, we provide a nuanced understanding on the strengths and weaknesses of each repair strategy.
Title: Crowdlicit: A System for Conducting Distributed End-User Elicitation and Identification Studies
Authors: family: Ali
given: Abdullah X.; family: Morris
given: Meredith Ringel; family: Wobbrock
given: Jacob O.
Venue: Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems
Keywords: mechanical turk, crowdsourcing, end-user identification study, end-user elicitation study, user-driven design

Abstract: End-user elicitation studies are a popular design method. Currently, such studies are usually confined to a lab, limiting the number and diversity of participants, and therefore the representativeness of their results. Furthermore, the quality of the results from such studies generally lacks any formal means of evaluation. In this paper, we address some of the limitations of elicitation studies through the creation of the Crowdlicit system along with the introduction of end-user identification studies, which are the reverse of elicitation studies. Crowdlicit is a new web-based system that enables researchers to conduct online and in-lab elicitation and identification studies. We used Crowdlicit to run a crowd-powered elicitation study based on Morris's "Web on the Wall" study (2012) with 78 participants, arriving at a set of symbols that included six new symbols different from Morris's. We evaluated the effectiveness of 49 symbols (43 from Morris and six from Crowdlicit) by conducting a crowd-powered identification study. We show that the Crowdlicit elicitation study resulted in a set of symbols that was significantly more identifiable than Morris's.
Title: Thinking Too Classically: Research Topics in Human-Quantum Computer Interaction
Authors: family: Ashktorab
given: Zahra; family: Weisz
given: Justin D.; family: Ashoori
given: Maryam
Venue: Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems
Keywords: quantum computing education, qhci, human-quantum computer interaction

Abstract: Quantum computing is a fundamentally different way of performing computation than classical computing. Many problems that are considered hard for classical computers may have efficient solutions using quantum computers. Recently, technology companies including IBM, Microsoft, and Google have invested in developing both quantum computing hardware and software to explore the potential of quantum computing. Because of the radical shift in computing paradigms that quantum represents, we see an opportunity to study the unique needs people have when interacting with quantum systems, what we call Quantum HCI (QHCI). Based on interviews with experts in quantum computing, we identify four areas in which HCI researchers can contribute to the field of quantum computing. These areas include understanding current and future quantum users, tools for programming and debugging quantum algorithms, visualizations of quantum states, and educational materials to train the first generation of "quantum native" programmers.
Title: Predicting Cognitive Load in Future Code Puzzles
Authors: family: Kelleher
given: Caitlin; family: Hnin
given: Wint
Venue: Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems
Keywords: cognitive load, code puzzles, adaptive learning system

Abstract: Code puzzles are an increasingly popular way to introduce youth to programming. Yet our knowledge about how to maximize learning from puzzles is incomplete. We conducted a data collection study and trained a model that predicts cognitive load, the mental effort necessary to complete a task, on a future puzzle. Controlling cognitive load can lead to more effective learning. Our model suggests that it is possible to predict Cognitive Load on future problems; the model could correctly distinguish the more difficult puzzle within a pair 71%-79% of the time. Further, studying the model itself provides new insights into the sources of puzzle difficulty, the factors that contribute to Cognitive Load, and their inter-relationships. Finally, the ability to predict Cognitive Load on a future puzzle is an important step towards the creation of adaptive code puzzle systems.
Title: Hey Google, Can I Ask You Something in Private?
Authors: family: Cho
given: Eugene
Venue: Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems
Keywords: voice assistant(s), conversational agent(s), information sensitivity, modality, privacy concerns, social presence, virtual assistant(s)

Abstract: MModern day voice-activated virtual assistants allow users to share and ask for information that could be considered as personal through different input modalities and devices. Using Google Assistant, this study examined if the differences in modality (i.e., voice vs. text) and device (i.e., smartphone vs. smart home device) affect user perceptions when users attempt to retrieve sensitive health information from voice assistants. Major findings from this study suggest that voice (vs. text) interaction significantly enhanced perceived social presence of the voice assistant, but only when the users solicited less sensitive health-related information. Furthermore, when individuals reported less privacy concerns, voice (vs. text) interaction elicited positive attitudes toward the voice assistant via increased social presence, but only in the low (vs. high) information sensitivity condition. Contrary to modality, the device difference did not exert any significant impact on the attitudes toward the voice assistant regardless of the sensitivity level of the health information being asked or the level of individuals' privacy concerns.
Title: Influencers in Multiplayer Online Shooters: Evidence of Social Contagion in Playtime and Social Play
Authors: family: Canossa
given: Alessandro; family: Azadvar
given: Ahmad; family: Harteveld
given: Casper; family: Drachen
given: Anders; family: Deterding
given: Sebastian
Venue: Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems
Keywords: influence, social network analysis, live games, online communities, games-as-services

Abstract: In a wide range of social networks, people's behavior is influenced by social contagion: we do what our network does. Networks often feature particularly influential individuals, commonly called "influencers." Existing work suggests that in-game social networks in online games are similar to real-life social networks in many respects. However, we do not know whether there are in-game equivalents to influencers. We therefore applied standard social network features used to identify influencers to the online multiplayer shooter Tom Clancy's The Division. Results show that network feature-defined influencers had indeed an outsized impact on playtime and social play of players joining their in-game network.
Title: Digital Financial Needs of Micro-entrepreneur Women in Pakistan: Is Mobile Money The Answer?
Authors: family: Mustafa
given: Maryam; family: Mazhar
given: Noor; family: Asghar
given: Ayesha; family: Usmani
given: Maryem Zafar; family: Razaq
given: Lubna; family: Anderson
given: Richard
Venue: Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems
Keywords: dfs, financial inclusion, low-resource, gender, women

Abstract: This paper studies the use of Digital Financial Services (DFS) as a solution to women's financial inclusion in deeply patriarchal, resource constrained communities. Through a qualitative, empirical study we map the financial life cycles of 20 women micro-entrepreneurs in different cities in Pakistan and the challenges they face. We explore how technology is currently influencing these women's businesses and personal lives and reveal how mobile money is not tuned to the problems they face and their financial needs. We present alternate design directions for meeting the technological and financial needs of these women, circumnavigating the patriarchal structures that constrain them.
Title: Understanding Mass-Market Mobile TV Behaviors in the Streaming Era
Authors: family: Bentley
given: Frank; family: Lottridge
given: Danielle
Venue: Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems
Keywords: smartphone, mobile, television, survey, streaming

Abstract: Despite claims of Mobile TV's mainstream arrival in 2010, it took until 2017 for watching professionally-produced television content on mobile phones to truly become a mass-market phenomenon in America, with half of all TV content expected to be watched on mobile phones by 2020. But what professionally produced content are people watching on their phones and when are they watching it? Are there any clusters of behavior that emerge in the broader population when it comes to watching TV on the phone? We set out to answer these questions through two surveys deployed to representative samples of online Americans. We discuss our findings on the mass-market arrival of mobile TV viewing and differences from how the HCI community has previously envisioned mobile video. We conclude with implications for the design of future mobile TV systems.
Title: Bringing Design to the Privacy Table: Broadening “Design” in “Privacy by Design” Through the Lens of HCI
Authors: family: Wong
given: Richmond Y.; family: Mulligan
given: Deirdre K.
Venue: Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems
Keywords: design research, privacy by design, critically oriented design, design approaches

Abstract: In calls for privacy by design (PBD), regulators and privacy scholars have investigated the richness of the concept of "privacy." In contrast, "design" in HCI is comprised of rich and complex concepts and practices, but has received much less attention in the PBD context. Conducting a literature review of HCI publications discussing privacy and design, this paper articulates a set of dimensions along which design relates to privacy, including: the purpose of design, which actors do design work in these settings, and the envisioned beneficiaries of design work. We suggest new roles for HCI and design in PBD research and practice: utilizing values- and critically-oriented design approaches to foreground social values and help define privacy problem spaces. We argue such approaches, in addition to current "design to solve privacy problems" efforts, are essential to the full realization of PBD, while noting the politics involved when choosing design to address privacy.
Title: Practitioners Teaching Data Science in Industry and Academia: Expectations, Workflows, and Challenges
Authors: family: Kross
given: Sean; family: Guo
given: Philip J.
Venue: Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems
Keywords: teaching programming, data science education

Abstract: Data science has been growing in prominence across both academia and industry, but there is still little formal consensus about how to teach it. Many people who currently teach data science are practitioners such as computational researchers in academia or data scientists in industry. To understand how these practitioner-instructors pass their knowledge onto novices and how that contrasts with teaching more traditional forms of programming, we interviewed 20 data scientists who teach in settings ranging from small-group workshops to large online courses. We found that: 1) they must empathize with a diverse array of student backgrounds and expectations, 2) they teach technical workflows that integrate authentic practices surrounding code, data, and communication, 3) they face challenges involving authenticity versus abstraction in software setup, finding and curating pedagogically-relevant datasets, and acclimating students to live with uncertainty in data analysis. These findings can point the way toward better tools for data science education and help bring data literacy to more people around the world.
Title: An Exploration of Speech-Based Productivity Support in the Car
Authors: family: Martelaro
given: Nikolas; family: Teevan
given: Jaime; family: Iqbal
given: Shamsi T.
Venue: Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems
Keywords: driving, productivity, multitasking, attention management

Abstract: In-car intelligent assistants offer the opportunity to help drivers productively use previously unclaimed time during their commute. However, engaging in secondary tasks can reduce attention on driving and thus may affect road safety. Any interface used while driving, even if speech-based, cannot consider non-driving tasks in isolation of driving---alerts for safer driving and timing of the non-driving tasks are crucial to maintaining safety. In this work, we explore experiences with a speech-based assistant that attempts to help drivers safely complete complex productivity tasks. Via a controlled simulator study, we look at how level of support and road context alerts from the assistant influence a driver's ability to drive safely while writing a document or creating slides via speech. Our results suggest ways to support speech-based productivity interactions and how speech-based road context alerts may influence driver behavior.