Effect of social Media on mental health

Abstract

An online community where people work together to produce, share and change their ideas and comments about any data is known as web-based social network ing. Over the past ten years, long-distance social networking purpose of connecting has profoundly changed how people interact and collaborate. This study aims to evaluate how social media expanded and opened doors to making social correlations that might add to psychological wellness challenges. It included inquiries for de mographic data, an example of long-range interpersonal communication use, social relationships, and well-being impacts. A descriptive study examined responses from 793 adults to a self-created questionnaire with four sections that was sent using the Google survey tool. In order to develop a paradigm concerning the Chi-Squared test has been used to know about the relationships between social networking site use and the three different categories of psychological distress which are depression, anxiety, loneliness. Previously, different methodologies and theories have been used to know about the effects of social media on mental health. We have tried using the supervised learning classifiers such as Random forest, Decision Tree, SVN, KNN, ADA Boost, Na¨ıve bayes and Voting classifier on the data set pertaining to the use of social networking sites and mental health issues which was dynamically examined. Among those classifiers we chose the best results with the highest accuracy and f1 scores as these results can tell us how much false positives and false negatives we get. Depending on the scores, we found that SVN classifier delivered the best results with an average accuracy score of 38% for depression, 48% for anxiety and 65% for loneliness and an F1 scores of 28%, 42% and 44% respectively.