MWAIS 2024 Proceedings
Abstract
The surge in smartphone usage has led to many mobile applications, notably mental health apps, offering tailored interventions. Reviews of these apps provide vital insights into users' emotions, perceptions, and experiences, highlighting satisfaction, concerns, and improvement areas. This study analyzed depression app reviews using sentiment analysis and topic modeling to improve user experience. Sentiment analysis was used to identify users' emotions (positive or negative), while the topic model was used to identify critical themes occurring in the reviews, focusing on negative reviews. Two major themes emerged from the analysis – Content issues, where users discussed the experience with the information provided by the apps, and technical issues, where users discussed functionalities. Addressing these concerns can enhance user experiences and optimize mental health apps to support well-being.
Recommended Citation
Okuboyejo, Senanu; Munmun, Mousumi; and Walczak, Steven, "Insights from Depression Apps User Reviews via Sentiment Analysis and Topic Modelling" (2024). MWAIS 2024 Proceedings. 3.
https://aisel.aisnet.org/mwais2024/3