Intention-use gaps and displacement of valued activities predict social media regret more strongly than duration, with pre-session context generalizing across users and physiological signals adding person-specific predictive power.
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Using Thematic Analysis in Psychology
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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.
SoulNote enables multi-session GenAI songwriting for DHH users, producing measurable gains in self-insight, emotion regulation, and self-care attitudes.
Open-ended preference data reveals substantial plurality in what people want from AI and divergent interpretations of shared values such as truthfulness.
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.
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.
Qualitative interviews with five Muslim women highlight the need for balanced, optional contextual links between Qur'an, Hadith, and Seerah in learning apps, leading to the concept of layered contextuality.
PAPEL, a parent-AI collaborative system with four modules grounded in play scenes, led to more integrated parent utterances and increased parent-child conversational turns in a study of 16 dyads compared to a chatbot baseline.
Biofoundries reshape scientific creativity by displacing sensory cues and redistributing responsibility, and should be designed as Creativity Support Tools based on interviews with nine experts.
Introduces Semantic Repulsion Technique (SRT) that boosts semantic diversity in AI creative outputs by 85-167% and receives higher usefulness and coherence ratings than baselines in a 16-person user study.
Mixed-methods study of agile teams finds fragmented practices and organizational barriers limit neurodivergent inclusion despite agile methods' potential.
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.
citing papers explorer
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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.
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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.