A Cross-Platform Dataset of COVID-19 Health Application Reviews from Google Play and Apple App Store

A curated dataset and analysis of COVID-19 mobile application reviews collected from both the Google Play Store and the Apple App Store across Android and iOS platforms. Researchers systematically collected reviews using automated scraping techniques, and standardized preprocessing was applied to clean and normalize the textual data. Dataset Variables Region — The broader geographical region (e.g., Asia, Europe) where the app store review originated. Country — The specific country associated with the user review, based on app store metadata. Code — A standardized country or region code for facilitating grouping and analysis. Name — The name of the COVID-19 mobile application from which the review was collected. Review — The raw user-submitted review text extracted from Google Play or the Apple App Store. dependency — Binary label indicating whether the review mentions dependency-related non-functional requirements (e.g., API issues, external service reliance). performance — Binary label identifying reviews referring to performance factors such as speed, latency, crashes, or resource usage. supportability — Binary indicator for maintainability, compatibility, installation issues, and update-related feedback. usability — Binary label marking reviews that contain user interface, user experience, accessibility, or navigation problems. miscellaneous — Binary label capturing NFR-related feedback that does not fall into the four main categories. source — The classification method used (e.g., SVM model, Gemini Pro annotation), documenting how the NFR label was assigned.