Prediction of Depression in Social Network Sites Using Data Mining
R Vanlalawmpuia, Mr Lalhmingliana
Abstract
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.