huashen218/convxai-cia-dataset huggingface dataset:
Title: Exploring the Role of Paradata in Digitally Supported Qualitative Co-Research
Authors: family: Rainey
given: Jay; family: Macfarlane
given: Siobhan; family: Puussaar
given: Aare; family: Vlachokyriakos
given: Vasilis; family: Burrows
given: Roger; family: Smeddinck
given: Jan David; family: Briggs
given: Pamela; family: Montague
given: Kyle
Venue: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems
Keywords: Citizen Research, Co-Research, Qualitative Practices, Paradata, Research Methods, Ethnography

Abstract: Academics and community organisations are increasingly adopting co-research practices where participants contribute to qualitative data collection, analysis, and dissemination. These qualitative practices can often lack transparency that can present a problem for stakeholders (such as funding agencies) who seek evidence of the rigour and accountability in these decision-making processes. When qualitative research is done digitally, paradata is available as interaction logs that reveal the underlying processes, such as the time spent engaging with different segments of an interview. In practice, paradata is seldom used to examine the decisions associated with undertaking qualitative research. This paper explores the role of paradata arising from a four-month engagement with a community-led charity that used a digital platform to support their qualitative co-research project. Through observations of platform use and reflective post-deployment interviews, our findings highlight examples of paradata generated through digital tools in qualitative research, e.g., listening coverage, engagement rate, thematic maps and data discards. From this, we contribute a conceptualisation of paradata and discuss its role in qualitative research to improve process transparency, enhance data sharing, and to create feedback loops with research participants.
Title: “It’s Freedom to Put Things Where My Mind Wants”: Understanding and Improving the User Experience of Structuring Data in Spreadsheets
Authors: family: Chalhoub
given: George; family: Sarkar
given: Advait
Venue: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems
Keywords: spreadsheets, data, user experience, structure

Abstract: Despite efforts to augment or replace the 2-dimensional spreadsheet grid with formal data structures such as arrays and tables to ease formula authoring and reduce errors, the flexible grid remains overwhelmingly successful. Why? We interviewed a diverse sample of 21 spreadsheet users about their use of structure in spreadsheets. It emerges that data structuring is subject to a complex network of incentives and constraints, including factors extrinsic to spreadsheets such as the user’s expertise, auxiliary tools, and collaborator needs. Moreover, we find that table columns are an important abstraction, and that operations such as conditional formatting, data validation, and formula authoring can be implemented on table columns, rather than cell ranges. To probe this, we designed 4 click-through prototypes for a follow-up study with 20 participants. We found that although column operations improved the value proposition of structured tables, they are unlikely to supplant the advantages of the flexible grid.
Title: Establishing Design Consensus toward Next-Generation Retail: Data-Enabled Design Exploration and Participatory Analysis
Authors: family: Yao
given: Yuan; family: Cai
given: Junai; family: Du
given: Kexin; family: Hou
given: Yuxuan; family: Mi
given: Haipeng
Venue: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems
Keywords: Design in Retail, Customer Behavior Understanding, Data-enabled Design, Participatory Data Analysis

Abstract: Integration of online and offline retail faces challenges in technology adoption, interaction style evolution and customer behavior shifts, while also being complicated by diverse perspectives from different stakeholders of consumers, retail staff, and retail business unit people. To explore how we can tackle the aforementioned challenges, this work applied the data-enabled design method and participatory data analysis to a case study, where 400 student consumers’ shopping behavior data was collected, cross-analyzed, and visualized in a campus chain store. We then invited 13 stakeholders to join a co-creation workshop for a further participatory data analysis. In the workshop, the different stakeholders came to a design consensuses which we summarized into a series of practical design recommendations for improving the current store. Finally, we generalized the case study process as a contextual-informed-aware model, which can contribute to professional design practice for the retail industry.
Title: The Deskilling of Domain Expertise in AI Development
Authors: family: Sambasivan
given: Nithya; family: Veeraraghavan
given: Rajesh
Venue: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems
Keywords: ML, field workers, Taylorism, deskilling, labour studies, data collection, domain expertise, data quality

Abstract: Field workers, like farmers and radiologists, play a crucial role in dataset collection for AI models in low-resource settings. However, we know little about how field workers’ expertise is leveraged in dataset and model development. Based on 68 interviews with AI developers building for low-resource contexts, we find that developers reduced field workers to data collectors. Attributing poor data quality to worker practices, developers conceived of workers as corrupt, lazy, non-compliant, and as datasets themselves, pursuing surveillance and gamification to discipline workers to collect better quality data. Even though models sought to emulate the expertise of field workers, AI developers treated workers as non-essential and deskilled their expertise in service of building machine intelligence. We make the case for why field workers should be recognised as domain experts and re-imagine domain expertise as an essential partnership for AI development.
Title: Understanding Challenges for Developers to Create Accurate Privacy Nutrition Labels
Authors: family: Li
given: Tianshi; family: Reiman
given: Kayla; family: Agarwal
given: Yuvraj; family: Cranor
given: Lorrie Faith; family: Hong
given: Jason I.
Venue: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems
Keywords: Privacy, iOS Development, Interview, Privacy Nutrition Label, Developer Study

Abstract: Apple announced the introduction of app privacy details to their App Store in December 2020, marking the first ever real-world, large-scale deployment of the privacy nutrition label concept, which had been introduced by researchers over a decade earlier. The Apple labels are created by app developers, who self-report their app’s data practices. In this paper, we present the first study examining the usability and understandability of Apple’s privacy nutrition label creation process from the developer’s perspective. By observing and interviewing 12 iOS app developers about how they created the privacy label for a real-world app that they developed, we identified common challenges for correctly and efficiently creating privacy labels. We discuss design implications both for improving Apple’s privacy label design and for future deployment of other standardized privacy notices.
Title: How Ready is Your Ready? Assessing the Usability of Incident Response Playbook Frameworks
Authors: family: Stevens
given: Rock; family: Votipka
given: Daniel; family: Dykstra
given: Josiah; family: Tomlinson
given: Fernando; family: Quartararo
given: Erin; family: Ahern
given: Colin; family: Mazurek
given: Michelle L.
Venue: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems
Keywords: incident response, security operations, usability of frameworks

Abstract: Incident response playbooks provide step-by-step guidelines to help security operations personnel quickly respond to specific threat scenarios. Although playbooks are common in the security industry, they have not been empirically evaluated for effectiveness. This paper takes a first step toward measuring playbooks and the frameworks used to design them, using two studies conducted in an enterprise environment. In the first study, twelve security professionals created two playbooks each, using two standard playbook design frameworks; the resulting playbooks were evaluated by experts for accuracy. In the second, we observed five personnel using the created playbooks in no-notice threat exercises within a live security-operations center. We find that playbooks can help simplify and support incident response efforts. However, playbooks designed using the frameworks we examined often lack sufficient detail for real-world use, particularly for more junior technicians. We provide recommendations for improving playbooks, playbook frameworks, and organizational processes surrounding playbook use.
Title: Recruiting Participants With Programming Skills: A Comparison of Four Crowdsourcing Platforms and a CS Student Mailing List
Authors: family: Tahaei
given: Mohammad; family: Vaniea
given: Kami
Venue: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems
Keywords: recruitment, datasets, usable privacy and security, developers, empirical software engineering, programming, crowdsourcing

Abstract: Reliably recruiting participants with programming skills is an ongoing challenge for empirical studies involving software development technologies, often leading to the use of crowdsourcing platforms and computer science (CS) students. In this work, we use five existing survey instruments to explore the programming skills, privacy and security attitudes, and secure development self-efficacy of participants from a CS student mailing list and four crowdsourcing platforms (Appen, Clickworker, MTurk, and Prolific). We recruited 613 participants who claimed to have programming skills and assessed recruitment channels regarding costs, quality, programming skills, as well as privacy and security attitudes. We find that 27% of crowdsourcing participants, 40% of crowdsourcing participants who self-report to be developers, and 89% of CS students answered all programming skill questions correctly. CS students were the most cost-effective recruitment channel and rated themselves lower than crowdsourcing participants about secure development self-efficacy.
Title: Impact and User Perception of Sandwich Attacks in the DeFi Ecosystem
Authors: family: Wang
given: Ye; family: Zuest
given: Patrick; family: Yao
given: Yaxing; family: Lu
given: Zhicong; family: Wattenhofer
given: Roger
Venue: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems

Abstract: Decentralized finance (DeFi) enables crypto-asset holders to conduct complex financial transactions, while maintaining control over their assets in the blockchain ecosystem. However, the transparency of blockchain networks and the open mechanism of DeFi applications also cause new security issues. In this paper, we focus on sandwich attacks, where attackers take advantage of the transaction confirmation delay and cause financial losses for victims. We evaluate the impact and investigate users’ perceptions of sandwich attacks through a mix-method study. We find that due to users’ lack of technical background and insufficient notifications from the markets, many users were not aware of the existence and the impact of sandwich attacks. They also had a limited understanding of how to resolve the security issue. Interestingly, users showed high tolerance for the impact of sandwich attacks on individuals and the ecosystem, despite potential financial losses. We discuss general implications for users, DeFi applications, and the community.
Title: Maptimizer: Using Optimization to Tailor Tactile Maps to Users Needs
Authors: family: Hofmann
given: Megan; family: Mack
given: Kelly; family: Birchfield
given: Jessica; family: Cao
given: Jerry; family: Hughes
given: Autumn G; family: Kurpad
given: Shriya; family: Lum
given: Kathryn J; family: Warnock
given: Emily; family: Caspi
given: Anat; family: Hudson
given: Scott E; family: Mankoff
given: Jennifer
Venue: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems
Keywords: low-vision, ability based design, blind, navigation, optimization, generative design, tactile graphics, 3D printing

Abstract: Tactile maps can help people who are blind or have low-vision navigate and familiarize themselves with unfamiliar locations. Ideally, tactile maps can be customized to an individual’s unique needs and abilities because of their limited space for representation. We present Maptimizer, a tool that generates tactile maps based on users’ preferences and requirements. Maptimizer uses a two stage optimization process to pair representations with geographic information and tune those representations to present that information more clearly. In a small user study, Maptimizer helped participants more successfully and efficiently identify locations of interest in unknown areas. These results demonstrate the utility of optimization techniques and generative design in complex accessibility domains.
Title: “It’s not wrong, but I’m quite disappointed”: Toward an Inclusive Algorithmic Experience for Content Creators with Disabilities
Authors: family: Choi
given: Dasom; family: Lee
given: Uichin; family: Hong
given: Hwajung
Venue: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems
Keywords: people with disabilities, YouTube, inclusive design, content creators, algorithmic experience

Abstract: YouTube is a space where people with disabilities can reach a wider online audience to present what it is like to have disabilities. Thus, it is imperative to understand how content creators with disabilities strategically interact with algorithms to draw viewers around the world. However, considering that the algorithm carries the risk of making less inclusive decisions for users with disabilities, whether the current algorithmic experiences (AXs) on video platforms is inclusive for creators with disabilities is an open question. To address that, we conducted semi-structured interviews with eight YouTubers with disabilities. We found that they aimed to inform the public of diverse representations of disabilities, which led them to work with algorithms by strategically portraying disability identities. However, they were disappointed that the way the algorithms work did not sufficiently support their goals. Based on findings, we suggest implications for designing inclusive AXs that could embrace creators’ subtle needs.
Title: TronicBoards: An Accessible Electronics Toolkit for People with Intellectual Disabilities
Authors: family: Senaratne
given: Hashini; family: Ananthanarayan
given: Swamy; family: Ellis
given: Kirsten
Venue: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems
Keywords: Electronics Toolkit, Intellectual Disabilities, Accessibility, Computational toolkit

Abstract: Engagement with electronic toolkits enhances people’s creative abilities, self-esteem, problem-solving skills and enables the creation of personally meaningful artifacts. A variety of simplified electronics toolkits are increasingly available to help different user groups engage with technology. However, they are often inaccessible for people with intellectual disabilities (IDs), who experience a range of cognitive and physical impairments. We designed and developed TronicBoards, a curated set of accessible electronic modules, to address this gap. We evaluated it one-on-one with 10 participants using a guided exploration approach. Our analysis revealed that participants were able to create simple sensor-based interactive circuits with varying levels of assistance. We report the strengths and weaknesses of TronicBoards, considering participants’ successes and challenges in manipulating and comprehending toolkit components, circuit building activities, and troubleshooting processes. We discuss implications for designing inclusive electronics toolkits for people with IDs, particularly in considering design elements that improve functionality, comprehensibility and agency.
Title: What makes web data tables accessible? Insights and a tool for rendering accessible tables for people with visual impairments
Authors: family: Wang
given: Yanan; family: Wang
given: Ruobin; family: Jung
given: Crescentia; family: Kim
given: Yea-Seul
Venue: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems
Keywords: Individuals with Disabilities & Assistive Technologies, Data Tables, Accessibility, Artifact or System, Empirical study that tells us about how people use a system

Abstract: The data table is a basic but versatile representation to communicate data. From government reports to bank statements, tables effectively carry essential data-driven information by visually organizing data using rows, columns, and other arrangements (e.g., merged cells). However, many tables online neglect the accessibility requirements for people who rely on screen readers, such as people who are blind or have low vision (BLV). First, we consolidated guidelines to understand what makes a table inaccessible for BLV people. We conducted an interview study to understand the importance of tables and identify further design requirements for an accessible table. We built a tool that automatically detects HTML formatted tables online and transforms them into accessible tables. Our evaluative study demonstrates how our tool can help participants understand the table’s structure and layout and support smooth navigation when the table is large and complex.
Title: CollabAlly: Accessible Collaboration Awareness in Document Editing
Authors: family: Lee
given: Cheuk Yin Phipson; family: Zhang
given: Zhuohao; family: Herskovitz
given: Jaylin; family: Seo
given: JooYoung; family: Guo
given: Anhong
Venue: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems
Keywords: Blind, voice font, earcon, accessibility, spatial audio, screen reader, visual impairment, collaboration awareness, Collaborative writing

Abstract: Collaborative document editing tools are widely used in professional and academic workplaces. While these tools provide basic accessibility support, it is challenging for blind users to gain collaboration awareness that sighted people can easily obtain using visual cues (e.g., who is editing where and what). Through a series of co-design sessions with a blind coauthor, we identified the current practices and challenges in collaborative editing, and iteratively designed CollabAlly, a system that makes collaboration awareness in document editing accessible to blind users. CollabAlly extracts collaborator, comment, and text-change information and their context from a document and presents them in a dialog box to provide easy access and navigation. CollabAlly uses earcons to communicate background events unobtrusively, voice fonts to differentiate collaborators, and spatial audio to convey the location of document activity. In a study with 11 blind participants, we demonstrate that CollabAlly provides improved access to collaboration awareness by centralizing scattered information, sonifying visual information, and simplifying complex operations.
Title: Data Every Day: Designing and Living with Personal Situated Visualizations
Authors: family: Bressa
given: Nathalie; family: Vermeulen
given: Jo; family: Willett
given: Wesley
Venue: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems
Keywords: situated visualization, self-tracking, personal data

Abstract: We explore the design and utility of situated manual self-tracking visualizations on dedicated displays that integrate data tracking into existing practices and physical environments. Situating self-tracking tools in relevant locations is a promising approach to enable reflection on and awareness of data without needing to rely on sensorized tracking or personal devices. In both a long-term autobiographical design process and a co-design study with six participants, we rapidly prototyped and deployed 30 situated self-tracking applications over a ten month period. Grounded in the experience of designing and living with these trackers, we contribute findings on logging and data entry, the use of situated displays, and the visual design and customization of trackers. Our results demonstrate the potential of customizable dedicated self-tracking visualizations that are situated in relevant physical spaces, and suggest future research opportunities and new potential applications for situated visualizations.
Title: Supporting Data-Driven Basketball Journalism through Interactive Visualization
Authors: family: Fu
given: Yu; family: Stasko
given: John
Venue: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems
Keywords: user interface, sports data visualization, data-driven journalism

Abstract: Basketball writers and journalists report on the sport that millions of fans follow and love. However, the recent emergence of pervasive data about the sport and the growth of new forms of sports analytics is changing writers’ jobs. While these writers seek to leverage the data and analytics to create engaging, data-driven stories, they typically lack the technical background to perform analytics or efficiently explore data. We investigated and analyzed the work and context of basketball writers, interviewed nine stakeholders to understand the challenges from a holistic view. Based on what we learned, we designed and constructed two interactive visualization systems that support rapid and in-depth sports data exploration and sense-making to enhance their articles and reporting. We deployed the systems during the recent NBA playoffs to gather initial feedback. This article describes the visualization design study we conducted, the resulting visualization systems, and what we learned to potentially help basketball writers in the future.
Title: Cicero: A Declarative Grammar for Responsive Visualization
Authors: family: Kim
given: Hyeok; family: Rossi
given: Ryan; family: Du
given: Fan; family: Koh
given: Eunyee; family: Guo
given: Shunan; family: Hullman
given: Jessica; family: Hoffswell
given: Jane
Venue: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems
Keywords: Visualization, responsive visualization, grammar

Abstract: Designing responsive visualizations can be cast as applying transformations to a source view to render it suitable for a different screen size. However, designing responsive visualizations is often tedious as authors must manually apply and reason about candidate transformations. We present Cicero, a declarative grammar for concisely specifying responsive visualization transformations which paves the way for more intelligent responsive visualization authoring tools. Cicero’s flexible specifier syntax allows authors to select visualization elements to transform, independent of the source view’s structure. Cicero encodes a concise set of actions to encode a diverse set of transformations in both desktop-first and mobile-first design processes. Authors can ultimately reuse design-agnostic transformations across different visualizations. To demonstrate the utility of Cicero, we develop a compiler to an extended version of Vega-Lite, and provide principles for our compiler. We further discuss the incorporation of Cicero into responsive visualization authoring tools, such as a design recommender.