Analysis of User Perception regarding the Mobile Healthcare Application of a Public Health Center using Big Data

PURPOSE This study aimed to investigate user perceptions regarding the mobile healthcare application of public health centers by using big data. METHODS The data included 1,089 users’ reviews (from September 27, 2016 December 23, 2021), which were analyzed Python, Textom, KrKwic, UCINET 6, and Net-draw program. RESULTS First, evaluation showed a higher number “Good” responses (677 times) compared “Bad” (329 “Normal” (83 times). Second, network structures related “Like,” “Health care,” “Help,” “A sense purpose,” “Grateful,” “Diet management,” “Exercise “Easy,” “Recommendation,” “Satisfaction,” “Diet,” “Useful,” so on. Third, “Execution error,” “Request improvement,” “Question,” “Slow speed,” “Interlocking “Lack food type,” “Login “Inconvenience,” “Delete reinstall,” “Update “Irritation,” “Connection “Problem occurred,” “Direct input request,” “Not available,” “Waste stars,” function,” enough,” “Stuffy,” exercise,” Fourth, as result structural equivalence analysis, four clusters appeared: cluster 1 (negative function), 2 emotion), 3 (positive 4 emotion). CONCLUSIONS It is necessary respond quickly in order reflect on reviews, active efforts are required improve program quality that users can use it conveniently.