Automated Emotional Quotient Detection in Social Media

Mental illness affects people all around the world that interfere with their reasoning and behaviour. An accurate identification of these disorders is difficult but critical, as it may increase the chances of providing support to people before their disease worsens. One way to accomplish this is to monitor how people present themselves online, such as what and how they write, or perhaps more importantly, what feelings they express in their virtual entertainment correspondences. In this study, we look at two computational representations that try to show the existence and variations of sensations expressed by web-based entertainment users. Mental disorders, Emotional patterns, Machine learning are the terms used in this file