An Advance Data Mining Approach on Gaming Addiction of Teen Age in Modern Era

Abstract

Addiction is a complex condition characterized by the compulsive use of a substance or engagement in a behavior despite negative consequences. Determining addiction involves assessing an individual's patterns of substance use or behavior, as well as any related physical, psychological, and social problems. This assessment can include interviews, self-report measures, and physiological tests. There are a huge number of internet users world-wide. Almost every mobile user has a mobile game installed on their mobile. Most of mobile users play mobile games, while adolescents are very specific and keen users of mobile games. Around 67% of people use mobile devices globally. A mobile game is installed on almost every user's device.. This essay discusses teen mobile game addiction and the differences between computer games, video games, console games, and Employing data mining tools, it examines the effects of mobile games on male teenagers, both good and negative. Video games are age and gender appropriate, very popular, but like other enjoyable activities, they can have negative effects, which are discussed.. Research on Internet addiction has shown that users can become addicted to it. In this paper, we’ve collected data to see the user is game addicted or not . For that reason after collecting data we pre processed data set and used 3 types of algorithms. Here we’ve used Gradient Boosting Classifier, Decision tree Classifier and Random Forest. The best accuracy was 83% which was got with the help of Radom forest. After getting best accuracy we also test the data with the help of algorithms.