Predicting Reels Addiction Using Machine Learning

The problem of Reels video addiction is on the rise, particularly among young people. Through the use of machine learning, this study aims to predict Reels video addiction. The dataset used in this study contains characteristics including age, gender, social media platform use, Reels video usage behaviors, and indicators of addiction. The research discovered that Reels video addiction is significantly predicted by these factors. Using machine learning models we apply 6 algorithms including Logistic Regression, SVC, Naive Bayes, Decision Tree, and Random Forest Classifier is given 79 percent accuracy, K-nearest neighbor give 71 percent accuracy. Those models predict and understand the factor in Reels addiction providing a suggestion to solve the problem.