WhatIf provides an interactive platform for real-time exploration of LLM-driven social simulations, enabling policymakers to iteratively test plans, reflect on assumptions, and uncover vulnerabilities in emergency preparedness scenarios.
mega hub Mixed citations
Using thematic analysis in psychology
Mixed citation behavior. Most common role is method (64%).
hub tools
citation-role summary
citation-polarity summary
authors
mega hub controls
Recognition alignment
counterfactual ablation
co-cited works
representative citing papers
SoulNote enables multi-session GenAI songwriting for DHH users, producing measurable gains in self-insight, emotion regulation, and self-care attitudes.
A participatory red-teaming project in the Global South created the PLACES dataset of 26k T2I failure examples that reveal unique cultural and linguistic harms missed by existing safety frameworks.
LLM facilitators in real-stakes group charity decisions shift specific allocations without raising consensus or participation equity, yet increase perceived trust and preference for the process.
Users entangle their lived experiences with AI predictions in menstrual tracking apps, leading to self-fulfilling prophecies, limited critical awareness from UI, and isolation for non-normative users.
A survey of 457 papers yields a six-dimensional design space for abstraction in interactive systems that reframes gulfs of execution and evaluation while articulating cognitive and design processes for bridging abstraction gaps.
LLM-based conversational interface for Android reduces task time and mental effort for blind users versus traditional gesture-based screen readers like TalkBack.
A scoping review and empirical analysis produce a six-category taxonomy of factors driving AI non-development and abandonment, showing that practical issues like resource limits and organizational dynamics often outweigh ethical concerns in real decisions.
AI improves brainstorming quality for general-purpose impact assessment but not specialized applications when it offers hints early and structures ideas later, based on workshop evaluations with 54 participants.
ANVIL automates analogy-based instructional animations for computer science by chaining LLM analogy generation, screenplay structuring, manim code production with repair, and mixed human-automated evaluations.
Interviews with practitioners and educators yield a systematic account of annotation design considerations, trade-offs, and contextual judgments in visualization practice.
A four-year mixed-methods study of game-based systems for Indian CHWs yields eight design guidelines for sustained engagement, learning transfer, and contextual appropriateness in low-resource health training.
StreetDesignAI provides structured multi-persona feedback on cycling designs and a user study shows it broadens designers' grasp of diverse cyclist perspectives and improves design decision confidence.
PREFAB applies preference learning grounded in the peak-end rule to let users annotate only key affective change segments while interpolating the rest, reducing workload and improving confidence in a 25-participant study.
The authors conduct a systematic literature review and real-world analysis to define Crowdsourced Context Systems and map a six-aspect design space with normative implications.
A method merges codebooks via LLM and evaluates human and AI inductive coding with four new metrics on an online conversation dataset.
Longitudinal surveys show AI coding assistants reduce time on code writing but increase supervisory verification tasks, with stable productivity perceptions yet rising reports of worsened developer experience.
Post-editors changed one in three metaphors in NMT and LLM outputs for literary texts, rated quality poor, and found post-editing more laborious than original translation.
GPT produces click distributions significantly different from real humans in 53% of UX first-click tasks, with prompting techniques like personas and chain-of-thought failing to improve alignment.
Teachers disengage from AI agent creation after training due to systemic contradictions that thwart psychological needs rather than skill gaps, and a CHAT-SDT redesign can resolve this by boosting both capacity and willingness.
Cluster analysis of teacher multi-agent workflow designs reveals three archetypes where AI-TPACK emerges dynamically from systems thinking, pedagogical beliefs, and self-efficacy.
PEFT fine-tuning of Code Llama yields feedback on student Java bugs that students judge equal to ChatGPT and better than prompt engineering, using BLEU/ROUGE/BERTScore plus human ratings.
Creatives prefer self-experimentation over structured guidance for GenAI image tools to preserve creative freedom, even when guidance aids AI literacy.
Large-scale review of 5300 AI incident reports shows harms are amplified up to three times at specific intersections including adolescent girls, lower-class people of color, and upper-class political elites.
citing papers explorer
-
WhatIf: Interactive Exploration of LLM-Powered Social Simulations for Policy Reasoning
WhatIf provides an interactive platform for real-time exploration of LLM-driven social simulations, enabling policymakers to iteratively test plans, reflect on assumptions, and uncover vulnerabilities in emergency preparedness scenarios.
-
From Daily Song to Daily Self: Supporting Reflective Songwriting of Deaf and Hard-of-Hearing Individuals through Generative Music AI
SoulNote enables multi-session GenAI songwriting for DHH users, producing measurable gains in self-insight, emotion regulation, and self-care attitudes.
-
Going PLACES: Participatory Localized Red Teaming for Text-to-Image Safety in the Global South
A participatory red-teaming project in the Global South created the PLACES dataset of 26k T2I failure examples that reveal unique cultural and linguistic harms missed by existing safety frameworks.
-
Real-Time Group Dynamics with LLM Facilitation: Evidence from a Charity Allocation Task
LLM facilitators in real-stakes group charity decisions shift specific allocations without raising consensus or participation equity, yet increase perceived trust and preference for the process.
-
"It became a self-fulfilling prophecy": How Lived Experiences are Entangled with AI Predictions in Menstrual Cycle Tracking Apps
Users entangle their lived experiences with AI predictions in menstrual tracking apps, leading to self-fulfilling prophecies, limited critical awareness from UI, and isolation for non-normative users.
-
Making Abstraction Concrete: A Design Space and Interaction Model of Abstraction in Interactive Systems
A survey of 457 papers yields a six-dimensional design space for abstraction in interactive systems that reframes gulfs of execution and evaluation while articulating cognitive and design processes for bridging abstraction gaps.
-
Insight: Enhancing Mobile Accessibility for Blind and Visually Impaired Users with LLMs
LLM-based conversational interface for Android reduces task time and mental effort for blind users versus traditional gesture-based screen readers like TalkBack.
-
To Build or Not to Build? Factors that Lead to Non-Development or Abandonment of AI Systems
A scoping review and empirical analysis produce a six-category taxonomy of factors driving AI non-development and abandonment, showing that practical issues like resource limits and organizational dynamics often outweigh ethical concerns in real decisions.
-
When and How AI Should Assist Brainstorming for AI Impact Assessment
AI improves brainstorming quality for general-purpose impact assessment but not specialized applications when it offers hints early and structures ideas later, based on workshop evaluations with 54 participants.
-
ANVIL: Analogies and Videos for Lecturers
ANVIL automates analogy-based instructional animations for computer science by chaining LLM analogy generation, screenplay structuring, manim code production with repair, and mixed human-automated evaluations.
-
Designing Annotations in Visualization: Considerations from Visualization Practitioners and Educators
Interviews with practitioners and educators yield a systematic account of annotation design considerations, trade-offs, and contextual judgments in visualization practice.
-
Design Guidelines for Game-Based Refresher Training of Community Health Workers in Low-Resource Contexts
A four-year mixed-methods study of game-based systems for Indian CHWs yields eight design guidelines for sustained engagement, learning transfer, and contextual appropriateness in low-resource health training.
-
StreetDesignAI: Broadening Designer Perspectives Through Multi-Persona Evaluation of Cycling Infrastructure
StreetDesignAI provides structured multi-persona feedback on cycling designs and a user study shows it broadens designers' grasp of diverse cyclist perspectives and improves design decision confidence.
-
PREFAB: PREFerence-based Affective Modeling for Low-Budget Self-Annotation
PREFAB applies preference learning grounded in the peak-end rule to let users annotate only key affective change segments while interpolating the rest, reducing workload and improving confidence in a 25-participant study.
-
Beyond Community Notes: A Framework for Understanding and Building Crowdsourced Context Systems for Social Media
The authors conduct a systematic literature review and real-world analysis to define Crowdsourced Context Systems and map a six-aspect design space with normative implications.
-
A Computational Method for Measuring "Open Codes" in Qualitative Analysis
A method merges codebooks via LLM and evaluates human and AI inductive coding with four new metrics on an online conversation dataset.
-
The Impact of AI Coding Assistants on Software Engineering: A Longitudinal Study
Longitudinal surveys show AI coding assistants reduce time on code writing but increase supervisory verification tasks, with stable productivity perceptions yet rising reports of worsened developer experience.
-
Metaphors in Literary Post-Editing: Opening Pandora's Box?
Post-editors changed one in three metaphors in NMT and LLM outputs for literary texts, rated quality poor, and found post-editing more laborious than original translation.
-
What Would GPT Click: Practical Effects of Human-AI Behavioral Misalignment and the Cost of Synthetic Participants in User Experience
GPT produces click distributions significantly different from real humans in 53% of UX first-click tasks, with prompting techniques like personas and chain-of-thought failing to improve alignment.
-
An Activity-Theoretical Approach to Teacher Professional Development in Pedagogical AI Agent Design
Teachers disengage from AI agent creation after training due to systemic contradictions that thwart psychological needs rather than skill gaps, and a CHAT-SDT redesign can resolve this by boosting both capacity and willingness.
-
Modeling AI-TPACK in Practice Insights from Teachers Multi-Agent Workflow Design
Cluster analysis of teacher multi-agent workflow designs reveals three archetypes where AI-TPACK emerges dynamically from systems thinking, pedagogical beliefs, and self-efficacy.
-
Fine-Tuning Models for Automated Code Review Feedback
PEFT fine-tuning of Code Llama yields feedback on student Java bugs that students judge equal to ChatGPT and better than prompt engineering, using BLEU/ROUGE/BERTScore plus human ratings.
-
How Creatives Approach GenAI Image Generation: Tensions Between Structured Guidance, Self-Experimentation, and Creative Autonomy
Creatives prefer self-experimentation over structured guidance for GenAI image tools to preserve creative freedom, even when guidance aids AI literacy.
-
Why AI Harms Can't Be Fixed One Identity at a Time: What 5300 Incident Reports Reveal About Intersectionality
Large-scale review of 5300 AI incident reports shows harms are amplified up to three times at specific intersections including adolescent girls, lower-class people of color, and upper-class political elites.
-
Trust as a Situated User State in Social LLM-Based Chatbots: A Longitudinal Study of Snapchat's My AI
Trust in social LLM chatbots is a dynamic, situated user state that evolves through ongoing interactions rather than forming as a stable one-time judgment.
-
Audio Video Verbal Analysis (AVVA) for Capturing Classroom Dialogues
AVVA is a new framework adapting verbal analysis for classroom discourse with triangulation across ten steps and a four-criterion validation scheme for temporal stability, applied to 23 hours of recordings.
-
Language, Place, and Social Media: Geographic Dialect Alignment in New Zealand
New Zealand Reddit users link language to place and form contiguous speech communities with complex geographic alignment; Word2Vec embeddings reveal semantic variations and shifts in NZ English on a 4.26 billion word corpus.
-
NexusAI: Enabling Design Space Exploration of Ideas through Cognitive Abstraction and Functional Decomposition
NexusAI decomposes LLM inspirations into navigable functional fragments and abstractions to improve creative design space exploration, with a user study showing reduced cognitive overhead.
-
Twitch Third-Party Developers' Support Seeking and Provision Practices on Discord
Twitch third-party developers' support practices on Discord create platform labor via dependence on Twitch, cross-platform switching, and the need for bridging roles between informal community help and formal platform channels.
-
Foreign Domestic Workers' Perspectives on an LLM-Based Emotional Support tool for Caregiving Burden
Exploratory interviews reveal FDWs find LLM chatbots psychologically safe, linguistically flexible, and useful for reassurance and companionship.
-
Not a Collaborator or a Supervisor, but an Assistant: Striking the Balance Between Efficiency and Ownership in AI-incorporated Qualitative Data Analysis
Interviews with 16 qualitative researchers identify efficiency, ownership, and trust as key factors shaping preferences for AI as a supportive assistant rather than a full collaborator or supervisor in qualitative data analysis.
-
Vibe Coding in Product Teams: Reconfiguring AI-Assisted Workflows, Prototyping, and Collaboration
Interviews reveal a four-stage vibe coding workflow that accelerates prototyping while introducing tensions between quick efficiency and reflective design intention, plus asymmetries in trust and ownership.
-
Unpacking "Personal" Health Informatics for Proactive Collective Care
Mixed-methods research shows collective care practices are constrained by personal, relational, technological, and structural factors in existing PHI systems, leading to the CC-Proact operational map with three design levers and ten recommendations for collective health informatics.
-
Framing an AI with Values Reduces AI Reliance in AI-supported Writing Tasks
An online experiment finds that showing users an overview of an AI's values reduces reliance on AI suggestions during writing tasks.
-
Measuring Changes in Instructor Class Design and Student Learning After the Release of Large Language Models (LLMs)
A pilot mixed-methods study at one university uses surveys and pre/post-LLM grade data to document patterns in faculty course design and student learning outcomes after generative AI release.
-
Understanding Clinician Experiences with Game-Based Interventions for Autistic Children to Inform a Future Game Platform Focused on Improving Motor Skills
Therapist perspectives on game-based motor interventions for autistic children reveal rigidity issues, leading to a proposed modular customizable game platform.
-
Effects of Collaboration on the Performance of Interactive Theme Discovery Systems
The study introduces a framework and reports differences in consistency, cohesiveness, and correctness of themes produced under synchronous versus asynchronous collaboration across three interactive NLP tools.
- Inside Baseball: The Automated Ball-Strike System as an Object Lesson in Technological Rule Enforcement