Depression Detection Using Digital Traces on Social Media: A Knowledge-Aware Deep Learning Approach
Journal of Management Information Systems
Individuals potentially experiencing depression constantly share their symptoms, major life events, and treatments on social media. We propose a Deep Knowledge-Aware Depression Detection (DKDD) framework to accurately detect social media users at risk of depression and explain the critical factors that contribute to such detection.
Wenli Zhang is an assistant professor of information systems and business analytics at the Ivy College of Business. Her paper is published in the Journal of Management Information Systems.