A Comparative Analysis of Social Communication Applications using Aspect Based Sentiment Analysis

Google Play Store is a popular distribution channel with millions of applications. WhatsApp the most downloaded communication application on Store. A few months ago, changed its privacy policy, triggering wave user reviews outrage. Privacy essential in application; users are worried about their data security and privacy. computational system must be required to analyze user’s for authority make better policies. This study aims develop deep learning-based model automatically assessing that can adapted future analysis. We proposed learning methodology by using Aspect-based sentiment analysis (ABSA) utilizing app scraped from play store scrapper application. uses text mining technique ABSA reviews. For Topic extraction, we have used Latent Dirichlet Allocation (LDA) method Long Short-Term Memory (LSTM) topic classification. The results show our gives us promising outcome 90% accuracy LSTM model. use optimize applications adding more efficient features updating them.