Detection of Depression in Social Media via Twitter Using Machine learning Approach

Abstract

In recent year’s social media platforms plays a crucial role in our daily life. The content which share by users on social media replicate the user’s internal life. Folks wish to share daily life incidence like happy moments, joyful memories, and unhappiness on social media. These social network sites widely used for scientist to spot the principles of depression and observe them. Social media provides a new chance to remodel early depression intervention services mostly in young adults. The aim is to develop a project in which system is capable and analyze the syntactical markers related to onset and perpetual symptoms of depression. By using this system it is possible to develop an algorithm which predicts depression in effective manner to put out the approach that syntactical markers used in tweets are often utilized to frame statistical model which will effectively find and also predict depression in such a way that can integrate and extend ancient method of identification.