A big data analytics framework for detecting user-level depression from social networks

Xingwei Yang, Rhonda McEwen, Liza Robee Ong, Morteza Zihayat
January 2020

Abstract

This paper presents a big data analytics framework for detecting user-level depression from social networks, contributing to mental health monitoring and support.

Type
Journal article
Publication
International Journal of Information Management

This work applies big data analytics techniques to detect depression indicators from social network data.

Big Data Analytics Depression Detection Social Networks Mental Health User Analysis
Morteza Zihayat
Morteza Zihayat
Principal Investigator

Dr. Morteza Zihayat is a Canada Research Chair (CRC) in Human-Centered AI and Associate Professor at Toronto Metropolitan University, Faculty of Engineering and Architectural Science. He also holds appointments as Adjunct Associate Professor at the University of Waterloo (Management Sciences) and IBM Faculty Fellow at IBM Centre for Advanced Studies. He is the Director of the Human-Centered Machine Intelligence Lab.