Investing in Applications Based on Predictive Modeling

Abstract

Since 1983, the start of the mobile industry has led to some great inventions. Due to the rapid increase in technology, the world of mobile applications has grown stupendously. While some applications achieve great success both from rating and financial perspective, several applications do not perform well in the application store. This research attempts to develop a model for the prediction of app ratings based on several data points collected from multiple sources. The research is restricted to Android apps, and the ratings are predicted using Linear Regression and Logistic Regression. The study brings in a new perspective of review sentiment and analyzes the impact of various parameters on the successful ratings of mobile applications.