GOOGLE PLAYSTORE REVIEWS (NLP) PREDICTION USING ML. - C., MsAbinaya; S., Pavithra; A., Elakiya (Proteus, 2022)
Google Play Store, Google's app store, is being used by millions of people on a daily basis. It is intended to access, among other things, publications, games, music, movies, and even television. After installing apps, users can submit reviews in the app store to share their personal experiences with others, and this works both ways, with one user being motivated by the ratings of others. The app's usability, performance, and, in rare cases, faults that users have faced while using it are usually explained by users' experiences. The goal is to use Supervised Machine Learning Techniques to classify Google app reviews (SMLT). The SMLT approaches are used to collect variable identification such as sentiments and sentiment polarity, as well as to create a dataset with these variables. It will then go through a series of stages, including data validation and cleaning, visualization, and classification into good, neutral, and negative sensations.