Age Matters: Analyzing Age-Related Discussions in App Reviews

2026-01-01

Journal of Systems and Software

AI Summary

This study addresses a significant gap in mobile application design: the lack of systematic understanding of age-related usability barriers that hinder inclusive user experiences across different age groups. To bridge this gap, the authors construct and annotate a large-scale dataset comprising 4,163 age-related reviews from Google Play—the first of its kind—and employ mixed-methods analysis to identify six core themes reflecting user concerns tied to age. They further evaluate eight classification models, including RoBERTa, for automated detection of age-related issues, with the best-performing model achieving a precision of 92.46%. The findings offer empirical grounding and actionable insights for age-inclusive design, advancing the development of mobile applications that better serve users of all ages.

Technology Category

• Humans and AI: User Experience and Usability
• Search and Optimization: Applications
• Cognitive Modeling & Cognitive Systems: Applications

Application Category

• User Modeling, Personalization and Recommendation: User privacy protection in personalized systems
• Search and Retrieval-Augmented AI: Web evaluation methodologies and metrics
• Systems and Infrastructure for Web, Mobile and WoT: Applied ML and AI for Web-based mobile applications

Problem

• age-related issues
• mobile apps
• user needs
• app usability
• age inclusivity

Innovation

• age-inclusive design
• app review analysis
• RoBERTa
• automated age-discussion detection
• user experience across age groups