huashen218/convxai-cia-dataset huggingface dataset:
Title: Fake News on Facebook and Twitter: Investigating How People (Don't) Investigate
Authors: family: Geeng
given: Christine; family: Yee
given: Savanna; family: Roesner
given: Franziska
Venue: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Abstract: With misinformation proliferating online and more people getting news from social media, it is crucial to understand how people assess and interact with low-credibility posts. This study explores how users react to fake news posts on their Facebook or Twitter feeds, as if posted by someone they follow. We conducted semi-structured interviews with 25 participants who use social media regularly for news, temporarily caused fake news to appear in their feeds with a browser extension unbeknownst to them, and observed as they walked us through their feeds. We found various reasons why people do not investigate low-credibility posts, including taking trusted posters' content at face value, as well as not wanting to spend the extra time. We also document people's investigative methods for determining credibility using both platform affordances and their own ad-hoc strategies. Based on our findings, we present design recommendations for supporting users when investigating low-credibility posts.
Title: Bot in the Bunch: Facilitating Group Chat Discussion by Improving Efficiency and Participation with a Chatbot
Authors: family: Kim
given: Soomin; family: Eun
given: Jinsu; family: Oh
given: Changhoon; family: Suh
given: Bongwon; family: Lee
given: Joonhwan
Venue: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Abstract: Although group chat discussions are prevalent in daily life, they have a number of limitations. When discussing in a group chat, reaching a consensus often takes time, members contribute unevenly to the discussion, and messages are unorganized. Hence, we aimed to explore the feasibility of a facilitator chatbot agent to improve group chat discussions. We conducted a needfinding survey to identify key features for a facilitator chatbot. We then implemented GroupfeedBot, a chatbot agent that could facilitate group discussions by managing the discussion time, encouraging members to participate evenly, and organizing members' opinions. To evaluate GroupfeedBot, we performed preliminary user studies that varied for diverse tasks and different group sizes. We found that the group with GroupfeedBot appeared to exhibit more diversity in opinions even though there were no differences in output quality and message quantity. On the other hand, GroupfeedBot promoted members' even participation and effective communication for the medium-sized group.
Title: Drone Chi: Somaesthetic Human-Drone Interaction
Authors: family: La Delfa
given: Joseph; family: Baytas
given: Mehmet Aydin; family: Patibanda
given: Rakesh; family: Ngari
given: Hazel; family: Khot
given: Rohit Ashok; family: Mueller
given: Florian 'Floyd'
Venue: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Abstract: Somaesthetics - motivated by improving life quality via appreciation for bodily and sensory experiences - is increasingly influencing HCI designs. Investigating the potential of drones as a material for somaesthetic HCI, we designed Drone Chi: a Tai Chi-inspired close-range human-drone interaction experience. The design process for Drone Chi has been informed by the soma design approach and the Somaesthetic Appreciation concept from HCI literature. The artifact expands somaesthetic HCI by exemplifying dynamic and intimate somaesthetic interactions with a robotic design material, and body movements in expansive 3D space. To characterize the Drone Chi experience, we conducted an empirical study with 32 participants. Analysis of participant accounts revealed 4 themes that articulate different aspects of the experience: Looping Mental States, Environment, Agency vs. Control, and Physical Narratives. From these accounts and our craft knowledge, we derive 5 design implications to guide the development of movement-based close-range drone interactions.
Title: Toward Immersive Self-Driving Simulations: Reports from a User Study across Six Platforms
Authors: family: Yeo
given: Dohyeon; family: Kim
given: Gwangbin; family: Kim
given: Seungjun
Venue: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Abstract: As self-driving car technology matures, autonomous vehicle research is moving toward building more human-centric interfaces and accountable experiences. Driving simulators avoid many ethical and regulatory concerns about self-driving cars and play a key role in testing new interfaces or autonomous driving scenarios. However, apart from validity studies for manual driving simulation, the capabilities of driving simulators in replicating the experience of self-driving cars have not been widely investigated. In this paper, we build six self-driving simulation platforms with varying levels of visual and motion fidelities ranging from a screen-based in-lab simulator to the mixed-reality on-road simulator we propose. We compare the sense of presence and simulator sickness for each simulator composition, as well as its visual and motion fidelities with a user study. Our novel mixed-reality automotive driving simulator, named MAXIM, showed highest fidelity and presence. Our findings suggest how visual and motion configurations affect experience in autonomous driving simulators.
Title: Would you do it?: Enacting Moral Dilemmas in Virtual Reality for Understanding Ethical Decision-Making
Authors: family: Niforatos
given: Evangelos; family: Palma
given: Adam; family: Gluszny
given: Roman; family: Vourvopoulos
given: Athanasios; family: Liarokapis
given: Fotis
Venue: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Abstract: A moral dilemma is a decision-making paradox without unambiguously acceptable or preferable options. This paper investigates if and how the virtual enactment of two renowned moral dilemmas---the Trolley and the Mad Bomber---influence decision-making when compared with mentally visualizing such situations. We conducted two user studies with two gender-balanced samples of 60 participants in total that compared between paper-based and virtual-reality (VR) conditions, while simulating 5 distinct scenarios for the Trolley dilemma, and 4 storyline scenarios for the Mad Bomber's dilemma. Our findings suggest that the VR enactment of moral dilemmas further fosters utilitarian decision-making, while it amplifies biases such as sparing juveniles and seeking retribution. Ultimately, we theorize that the VR enactment of renowned moral dilemmas can yield ecologically-valid data for training future Artificial Intelligence (AI) systems on ethical decision-making, and we elicit early design principles for the training of such systems.
Title: Choice of Voices: A Large-Scale Evaluation of Text-to-Speech Voice Quality for Long-Form Content
Authors: family: Cambre
given: Julia; family: Colnago
given: Jessica; family: Maddock
given: Jim; family: Tsai
given: Janice; family: Kaye
given: Jofish
Venue: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Abstract: The advancement of text-to-speech (TTS) voices and a rise of commercial TTS platforms allow people to easily experience TTS voices across a variety of technologies, applications, and form factors. As such, we evaluated TTS voices for long-form content: not individual words or sentences, but voices that are pleasant to listen to for several minutes at a time. We introduce a method using a crowdsourcing platform and an online survey to evaluate voices based on listening experience, perception of clarity and quality, and comprehension. We evaluated 18 TTS voices, three human voices, and a text-only control condition. We found that TTS voices are close to rivaling human voices, yet no single voice outperforms the others across all evaluation dimensions. We conclude with considerations for selecting text-to-speech voices for long-form content.
Title: StoryMakAR: Bringing Stories to Life With An Augmented Reality & Physical Prototyping Toolkit for Youth
Authors: family: Glenn
given: Terrell; family: Ipsita
given: Ananya; family: Carithers
given: Caleb; family: Peppler
given: Kylie; family: Ramani
given: Karthik
Venue: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Abstract: Makerspaces can support educational experiences in prototyping for children. Storytelling platforms enable high levels of creativity and expression, but have high barriers of entry. We introduce StoryMakAR, which combines making and storytelling. StoryMakAR is a new AR-IoT system for children that uses block programming, physical prototyping, and event-based storytelling to bring stories to life. We reduce the barriers to entry for youth (Age=14-18) by designing an accessible, plug-and-play system through merging both electro-mechanical devices and virtual characters to create stories. We describe our initial design process, the evolution and workflow of StoryMakAR, and results from multiple single-session workshops with 33 high school students. Our preliminary studies led us to understand what students want to make. We provide evidence of how students both engage and have difficulties with maker-based storytelling. We also discuss the potential for StoryMakAR to be used as a learning environment for classrooms and younger students.
Title: On Conducting Security Developer Studies with CS Students: Examining a Password-Storage Study with CS Students, Freelancers, and Company Developers
Authors: family: Naiakshina
given: Alena; family: Danilova
given: Anastasia; family: Gerlitz
given: Eva; family: Smith
given: Matthew
Venue: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Abstract: Ecological validity is a major concern in usable security studies with developers. Many studies are conducted with computer science (CS) students out of convenience, since recruiting professional software developers in sufficient numbers is very challenging. In a password-storage study, Naiakshina et al. (CHI'19) showed that CS students behave similarly to freelance developers recruited online. While this is a promising result for conducting developer studies with students, an open question remains: Do professional developers employed in companies behave similarly as well? To provide more insight into the ecological validity of recruiting students for security developer studies, we replicated the study of Naiakshina et al. with developers from diverse companies in Germany. We found that developers employed in companies performed better than students and freelancers in a direct comparison. However, treatment effects were found to be significant in all groups; the treatment effects on CS students also held for company developers.
Title: Researching AI Legibility through Design
Authors: family: Lindley
given: Joseph; family: Akmal
given: Haider Ali; family: Pilling
given: Franziska; family: Coulton
given: Paul
Venue: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Abstract: Everyday interactions with computers are increasingly likely to involve elements of Artificial Intelligence (AI). Encompassing a broad spectrum of technologies and applications, AI poses many challenges for HCI and design. One such challenge is the need to make AI's role in a given system legible to the user in a meaningful way. In this paper we employ a Research through Design (RtD) approach to explore how this might be achieved. Building on contemporary concerns and a thorough exploration of related research, our RtD process reflects on designing imagery intended to help increase AI legibility for users. The paper makes three contributions. First, we thoroughly explore prior research in order to critically unpack the AI legibility problem space. Second, we respond with design proposals whose aim is to enhance the legibility, to users, of systems using AI. Third, we explore the role of design-led enquiry as a tool for critically exploring the intersection between HCI and AI research.
Title: Modeling Organizational Culture with Workplace Experiences Shared on Glassdoor
Authors: family: Das Swain
given: Vedant; family: Saha
given: Koustuv; family: Reddy
given: Manikanta D.; family: Rajvanshy
given: Hemang; family: Abowd
given: Gregory D.; family: De Choudhury
given: Munmun
Venue: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Abstract: Organizational culture (OC) encompasses the underlying beliefs, values, and practices that are unique to an organization. However, OC is inherently subjective and a coarse construct, and therefore challenging to quantify. Alternatively, self-initiated workplace reviews on online platforms like Glassdoor provide the opportunity to leverage the richness of language to understand OC. In as much, first, we use multiple job descriptors to operationalize OC as a word vector representation. We validate this construct with language used in 650k different Glassdoor reviews. Next, we propose a methodology to apply our construct on Glassdoor reviews to quantify the OC of employees by sector. We validate our measure of OC on a dataset of 341 employees by providing empirical evidence that it helps explain job performance. We discuss the implications of our work in guiding tailored interventions and designing tools for improving employee functioning.
Title: Multimodal and Mixed Control of Robotic Endoscopes
Authors: family: Avellino
given: Ignacio; family: Bailly
given: Gilles; family: Arico
given: Mario; family: Morel
given: Guillaume; family: Canlorbe
given: Geoffroy
Venue: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Abstract: Bedside robotic endoscopes render surgeons autonomous from assistants, potentially improving surgical outcome and decreasing costs. Why then have they not been widely adopted? We take a step back and first characterize classic (non-robotic) endoscope use through observations, literature and a domain expert interview. We review the literature on bedside robotic endoscopes and find that existing controls, individually, do not have the power to support both intended and appropriated endoscope uses. We thus explore combining controls to support this diversity of uses. Through an iterative cycle, we design and implement a multimodal and mixed-initiative technique that combines two user controls and one system control. Our evaluations confirm that individual controls do not satisfy the diversity of endoscope uses, and also that our technique indeed does so. Our work highlights the relevance of HCI research in the medical domain through robotic systems.
Title: Virtual Field Studies: Conducting Studies on Public Displays in Virtual Reality
Authors: family: Mäkelä
given: Ville; family: Radiah
given: Rivu; family: Alsherif
given: Saleh; family: Khamis
given: Mohamed; family: Xiao
given: Chong; family: Borchert
given: Lisa; family: Schmidt
given: Albrecht; family: Alt
given: Florian
Venue: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Abstract: Field studies on public displays can be difficult, expensive, and time-consuming. We investigate the feasibility of using virtual reality (VR) as a test-bed to evaluate deployments of public displays. Specifically, we investigate whether results from virtual field studies, conducted in a virtual public space, would match the results from a corresponding real-world setting. We report on two empirical user studies where we compared audience behavior around a virtual public display in the virtual world to audience behavior around a real public display. We found that virtual field studies can be a powerful research tool, as in both studies we observed largely similar behavior between the settings. We discuss the opportunities, challenges, and limitations of using virtual reality to conduct field studies, and provide lessons learned from our work that can help researchers decide whether to employ VR in their research and what factors to account for if doing so.
Title: LIFT: Integrating Stakeholder Voices into Algorithmic Team Formation
Authors: family: Hastings
given: Emily M.; family: Alamri
given: Albatool; family: Kuznetsov
given: Andrew; family: Pisarczyk
given: Christine; family: Karahalios
given: Karrie; family: Marinov
given: Darko; family: Bailey
given: Brian P.
Venue: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Abstract: Team formation tools assume instructors should configure the criteria for creating teams, precluding students from participating in a process affecting their learning experience. We propose LIFT, a novel learner-centered workflow where students propose, vote for, and weigh the criteria used as inputs to the team formation algorithm. We conducted an experiment (N=289) comparing LIFT to the usual instructor-led process, and interviewed participants to evaluate their perceptions of LIFT and its outcomes. Learners proposed novel criteria not included in existing algorithmic tools, such as organizational style. They avoided criteria like gender and GPA that instructors frequently select, and preferred those promoting efficient collaboration. LIFT led to team outcomes comparable to those achieved by the instructor-led approach, and teams valued having control of the team formation process. We provide instructors and designers with a workflow and evidence supporting giving learners control of the algorithmic process used for grouping them into teams.
Title: Composing Flexibly-Organized Step-by-Step Tutorials from Linked Source Code, Snippets, and Outputs
Authors: family: Head
given: Andrew; family: Jiang
given: Jason; family: Smith
given: James; family: Hearst
given: Marti A.; family: Hartmann
given: Björn
Venue: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Abstract: Programming tutorials are a pervasive, versatile medium for teaching programming. In this paper, we report on the content and structure of programming tutorials, the pain points authors experience in writing them, and a design for a tool to help improve this process. An interview study with 12 experienced tutorial authors found that they construct documents by interleaving code snippets with text and illustrative outputs. It also revealed that authors must often keep related artifacts of source programs, snippets, and outputs consistent as a program evolves. A content analysis of 200 frequently-referenced tutorials on the web also found that most tutorials contain related artifacts—duplicate code and outputs generated from snippets—that an author would need to keep consistent with each other. To address these needs, we designed a tool called Torii with novel authoring capabilities. An in-lab study showed that tutorial authors can successfully use the tool for the unique affordances identified, and provides guidance for designing future tools for tutorial authoring.
Title: TurkEyes: A Web-Based Toolbox for Crowdsourcing Attention Data
Authors: family: Newman
given: Anelise; family: McNamara
given: Barry; family: Fosco
given: Camilo; family: Zhang
given: Yun Bin; family: Sukhum
given: Pat; family: Tancik
given: Matthew; family: Kim
given: Nam Wook; family: Bylinskii
given: Zoya
Venue: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Abstract: Eye movements provide insight into what parts of an image a viewer finds most salient, interesting, or relevant to the task at hand. Unfortunately, eye tracking data, a commonly-used proxy for attention, is cumbersome to collect. Here we explore an alternative: a comprehensive web-based toolbox for crowdsourcing visual attention. We draw from four main classes of attention-capturing methodologies in the literature. ZoomMaps is a novel zoom-based interface that captures viewing on a mobile phone. CodeCharts is a self-reporting methodology that records points of interest at precise viewing durations. ImportAnnots is an "annotation" tool for selecting important image regions, and cursor-based BubbleView lets viewers click to deblur a small area. We compare these methodologies using a common analysis framework in order to develop appropriate use cases for each interface. This toolbox and our analyses provide a blueprint for how to gather attention data at scale without an eye tracker.
Title: "I'm hoping they're an ethical company that won't do anything that I'll regret": Users Perceptions of At-home DNA Testing Companies
Authors: family: Baig
given: Khadija; family: Mohamed
given: Reham; family: Theus
given: Anna-Lena; family: Chiasson
given: Sonia
Venue: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Abstract: At-home DNA testing has become increasingly popular due to the ability to be able to gain both ancestry and health information, as well as connect with others who share your DNA. Do users have reasonable mental models of how these systems work? Do users have privacy concerns and what do they understand as the benefits and risks involved? We conducted 27 interviews with Canadian users of at-home DNA testing companies. Our interviews covered perceived and desired data use, data management, data sharing practices, control over data, and any regrets. Our qualitative analysis revealed that many users have inconsistencies in their mental models and liken their DNA data to their data stored with existing technologies, such as social media, rather than health data. They are generally either dismissive of privacy concerns towards themselves or their relatives or they had not considered privacy in their choice. We discuss our findings and propose possible future work in this area.
Title: Food Literacy while Shopping: Motivating Informed Food Purchasing Behaviour with a Situated Gameful App
Authors: family: Bomfim
given: Marcela C. C.; family: Kirkpatrick
given: Sharon I.; family: Nacke
given: Lennart E.; family: Wallace
given: James R.
Venue: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Abstract: Establishing healthy eating patterns early in life is critical and has implications for lifelong health. Situated interventions are a promising approach to improve eating patterns. However, HCI research has emphasized calorie control and weight loss, potentially leading consumers to prioritize caloric intake over healthy eating patterns. To support healthy eating more holistically, we designed a gameful app called Pirate Bri's Grocery Adventure (PBGA) that seeks to improve food literacy—meaning the interconnected combination of food-related knowledge, skills, and behaviours that empower an individual to make informed food choices— through a situated approach to grocery shopping. Findings from our three-week field study revealed that PBGA was effective for improving players' nutrition knowledge and motivation for healthier food choices and reducing their impulse purchases. Our findings highlight that nutrition apps should promote planning and shopping based on balance, variety, and moderation.