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Sushant Prabhu
Manipal Academy of Higher Education
Computer Science & IT Electrical & Electronics Engineering

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Journal : International Journal of Electrical and Computer Engineering

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Predicting depression using deep learning and ensemble algorithms on raw twitter data Nisha P. Shetty; Balachandra Muniyal; Arshia Anand; Sushant Kumar; Sushant Prabhu
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 4: August 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (545.735 KB) | DOI: 10.11591/ijece.v10i4.pp3751-3756

Abstract

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.
Co-Authors Arshia Anand Balachandra Muniyal Nisha P. Shetty Sushant Kumar