Digital Enterprise Seminar Series - Dr. Morteza Zihayat

Depression Detection Using User Generated Content in Social Media

Over 350 million people worldwide suffer from depression. A key part in diagnosing depression is screening questionnaires, which rely on patient self-reports of the recent past. With the advent of social media, there is an opportunity for a novel approach to detecting when a patient diagnosed with chronic depression becomes acute. In this project, we use social media data to detect depression acuity. Social media is indicative of an individual’s mental state. Our aim is to use machine learning to uncover patterns within the data to build a hybrid model to identify depression acuity more accurately and sooner than existing screening questionnaires. Read more about Dr. Morteza Zihayat (opens in new window) .