Depression Detection from Social Network using Machine Learning Techniques

  • Dr. D. T. Mane, Riticka Raajput, Muskan Shaikh, Balaji Devkar, Unmesh Chaudhari


Social network is a great platform for users to communicate, share their feelings, updates, sentiments. We can use this data to check whether the person is suffering from depression. In order to diagnose the depression, it can be divided into separate categories. In this paper, we focus on to perform depression detection on dataset which contains images related to post. To discover the impacts of sorrow, we created AI procedure as a proficient technique. We explored the execution of the proposed technique. We have checked the productivity of our proposed technique utilizing a lot of classification of Images. Our system can improve the accuracy and reduce the error. SVM gives better results than Machine Learning to detect the depression. Machine learning technique detects high accuracy of results of depressed user and will also categorize the type of depression among social network users.