Validation of Some Health Fitness Apps Using Users’ Reviews
Baale Abimbola Adebisi *
Ladoke Akintola University of Technology, Ogbomoso, Nigeria.
Alade Ridwan Olamide
Ladoke Akintola University of Technology, Ogbomoso, Nigeria.
Adigun Arafat Adeniyi
Federal University of Agriculture, Abeokuta, Nigeria.
*Author to whom correspondence should be addressed.
Abstract
With the increase in the number of Health Fitness Applications (Apps) available for free, there is a growing concern as to whether these apps actually help individuals achieve personal fitness. This research developed a system to validate three Health Fitness Apps before user download using user reviews.
Sentiment Analysis as the application of natural language processing, computational linguistics, and text analytics was used to identify and classify subjective opinions in the reviews of three most commonly used Health Fitness Applications; Samsung Health, Google Fit and Home Workout. Analysis showed that the Home Workout Fitness Application garnered a total of 99.9% Positive Reviews and can therefore be said to be the most effective of the three Apps considered, followed by Google Fit Fitness Application with a total of 37.4% Positive Reviews and Samsung Health Fitness Application recorded the most Negative Reviews of 96.6%.
Keywords: Health apps, fitness apps, sentiment analysis, opinion mining, users’ reviews, app validation