In recent years, mobile applications have become indispensable tools for managing various aspects of life. From enhancing productivity to providing personalized entertainment, mobile apps have revolutionized people's daily routines. Despite this rapid growth and popularity, gaps remain in how these apps address the needs of users from different age groups. Users of varying ages face distinct challenges when interacting with mobile apps, from younger users dealing with inappropriate content to older users having difficulty with usability due to age-related vision and cognition impairments. Although there have been initiatives to create age-inclusive apps, a limited understanding of user perspectives on age-related issues may hinder developers from recognizing specific challenges and implementing effective solutions. In this study, we explore age discussions in app reviews to gain insights into how mobile apps should cater to users across different age groups.We manually curated a dataset of 4,163 app reviews from the Google Play Store and identified 1,429 age-related reviews and 2,734 non-age-related reviews. We employed eight machine learning, deep learning, and large language models to automatically detect age discussions, with RoBERTa performing the best, achieving a precision of 92.46%. Additionally, a qualitative analysis of the 1,429 age-related reviews uncovers six dominant themes reflecting user concerns.

翻译：近年来，移动应用已成为管理生活各方面不可或缺的工具。从提升生产力到提供个性化娱乐，移动应用彻底改变了人们的日常生活。尽管移动应用增长迅速且广受欢迎，但这些应用在满足不同年龄段用户需求方面仍存在差距。不同年龄的用户在使用移动应用时面临不同的挑战：年轻用户需处理不当内容，而年长用户则可能因与年龄相关的视力及认知障碍而在可用性方面遇到困难。尽管已有创建全龄包容性应用的举措，但对用户年龄相关问题看法的有限理解，可能阻碍开发者识别具体挑战并实施有效解决方案。本研究通过分析应用评论中的年龄讨论，深入探讨移动应用应如何满足不同年龄段用户的需求。我们手动整理了一个包含4,163条Google Play商店应用评论的数据集，识别出1,429条年龄相关评论和2,734条非年龄相关评论。我们采用八种机器学习、深度学习和大语言模型来自动检测年龄讨论，其中RoBERTa表现最佳，精确率达到92.46%。此外，对1,429条年龄相关评论的定性分析揭示了反映用户关切的六个主要主题。