Prediction of Depression in Social Network Sites Using Data Mining

Social network Site has captured the attention of the young generation for the last past ten years. Through internet technology, it is becoming convenient and easy to access and interact with these social network sites with another side of the world. So, social network sites are now a source of mining data as large people are interacting and socializing with each other. Immense information relating to the user’s state of mind, feeling and negativism can also be extracted. Meanwhile, the Social network sites have been using to seek remedy for their worries not knowing they are having mental problems. Hence, Data mining gives a various way of techniques to retrieve relevant information and knowledge. And can also be used for statistical reports, machine learning and deep learning. These techniques introduce how to handle the retrieved data in the course of data analysis. This study has highlighted and revealed the user’s mental health status and condition by analyzing each user’s data. Analyzing data involves training each user’s data to get an output and also have a test set to get efficiency and accuracy. This study has brought out many depressive indicative words which play an important role to bring this study success. We also proposed some few methods that have been carried out in this study. Analyzation for efficiency has been performed using this proposed method which containing packages of emotional words and can also increase the accuracy, efficiency and the scale of analyzation lapse. Both these technology data mining and machine learning can give us the condition and status of the user’s mental health problem.

I. Introduction

[1] Elvis et al., mentioned that the people who are suffering from depression mostly wants to be isolated themselves from others, which makes them hope to find a solution in Social media by sharing their feelings and illness believing that would be able to give relief and able to take away their worries and anxieties. Instead, it has found that this social communication and sharing increases their worries and anxieties. Amongst many other social network sites Facebook is the fastest growing; In the worldwide, more than 2 billion users have an account in Social network sites [2]. And over 270 million Facebook members are from India, which makes the top country in terms of Facebook audience size [3]. Maximum users are used as a floor for socializing and presenting themselves which making this Facebook as the most online access sites [4]. Social network site (SNS) has made bold and high attention in the last past years since it was launched.