Smart Phone Addiction Prediction and Analysis

Abstract

The role of big data analytics in analysing smart phone addiction is changing in this age of rapidly advancing technology, as more and more people show signs of smartphone addiction, including overuse of phones, a decline in productivity, and potential issues with one’s physical and emotional well-being. The aim of this study was to identify the main arguments for the need for prediction analysis as well as if smartphone use might be utilized to forecast levels of smartphone addiction. wherein we will investigate the health issues that are expected to impact the individual. This research study has used the openly available dataset of smartphone usage by people and with a combination of machine learning algorithms as cat BOOST smartphone addiction level for effective decision making. According to the simulation results, cat boost algorithm achieved the best accuracy with a score 97.3