Investigating the Effects of Social Media on Mental Health

Social networks have indeed become an integral part of our lives, with more than 3 billion people catering to this network. Although it has many advantages for maintaining relationships with friends and families, spreading information, and accessing news and entertainment, it has also led to an alarming problem, i.e., negative effects on mental health. To understand the effect of social media on mental health, we have used the logistic regression model and Gaussian Bayes models to extract the important features. It contains a review of various research that addresses the issues of positive and negative impacts of social media, and examines the conclusions derived from these studies on public, policy, and clinical decision making. We have utilized Logistic Regression and Gaussian Bayes model for calculating the accuracy and performed a comparative study to find the better model. In the case of Logistic Regression it provides 99.3% accuracy and for the Gaussian Bayes model it is providing 94% accuracy. Study concludes, that logistic regression can better capture the features for understanding the effect of social media on mental health.