Age Matters: Analyzing Age-Related Discussions in App Reviews

TL;DR

This paper investigates how mobile app reviews reveal age-related user concerns, using machine learning models to automatically detect age discussions and analyzing themes to inform age-inclusive app design.

Contribution

It introduces a dataset of app reviews, applies advanced models for automatic detection of age-related discussions, and provides qualitative insights into user concerns across age groups.

Findings

RoBERTa achieved 92.46% precision in detecting age-related reviews.

Six dominant themes of user concerns were identified from qualitative analysis.

A dataset of 4,163 app reviews was curated for analysis.

Abstract

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.