COMPARATIVE STUDY ON PREDICTIVE ANALYSIS OF NO-APP-PHOBIA

Abstract

Technology's rise has facilitated growth but has also had a detrimental impact on humans. "No-App-Phobia" as we title it, based on an earlier study nomophobia, is characterized as fear and anxiety in those who cannot access any particular apps on their mobile phones. It could be due to various factors such as being unable to interact with their friends or family, feeling the loss of some entertainment, wanting to gain new information, and so on. WhatsApp, Instagram, Facebook, and Snapchat are the selected apps used for this study. In the suggested methodology, we take into account demographic variables and some NMP-Q i.e., Nomophobia Questionnaire as predictors of the ailment No-App-Phobia. This study aims to provide some insights into how people manage to live without the aforementioned mobile apps. To determine what level of No-App-Phobia a person suffers, this study uses a few Machine Learning Classification Algorithms. The findings of XGBoost have shown improved accuracy of 90.09% when compared to other current techniques like Random Forest, Decision Tree, and Gradient Boosting.