Predicting depression using deep learning and ensemble algorithms on raw twitter data

Nisha P. Shetty (Manipal Academy of Higher Education)
Balachandra Muniyal (Manipal Academy of Higher Education)
Arshia Anand (Manipal Academy of Higher Education)
Sushant Kumar (Manipal Academy of Higher Education)
Sushant Prabhu (Manipal Academy of Higher Education)

International Journal of Electrical and Computer Engineering
Vol 10, No 4: August 2020

Social network and microblogging sites such as Twitter are widespread amongst all generations nowadays where people connect and share their feelings, emotions, pursuits etc. Depression, one of the most common mental disorder, is an acute state of sadness where person loses interest in all activities. If not treated immediately this can result in dire consequences such as death. In this era of virtual world, people are more comfortable in expressing their emotions in such sites as they have become a part and parcel of everyday lives. The research put forth thus, employs machine learning classifiers on the twitter data set to detect if a person’s tweet indicates any sign of depression or not.