Predicting Depression Using Deep Learning and Ensemble Algorithms on Raw Twitter Data

Shetty, Nisha P and Muniyal, Balachandra and Anand, Arshia and Kumar, Sushant and Prabhu, Sushant (2020) Predicting Depression Using Deep Learning and Ensemble Algorithms on Raw Twitter Data. International Journal of Electrical and Computer Engineering, 10 (1). ISSN 2088-8708

[img] PDF
8507.pdf - Published Version
Restricted to Registered users only

Download (826kB) | Request a copy
Official URL: http://ijece.iaescore.com/index.php/IJECE

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

Item Type: Article
Uncontrolled Keywords: Depression, Machine Learning, Social Media, LSTM, Sentiment Analysis
Subjects: Engineering > MIT Manipal > Information and Communication Technology
Depositing User: MIT Library
Date Deposited: 25 Jun 2020 10:06
Last Modified: 25 Jun 2020 10:06
URI: http://eprints.manipal.edu/id/eprint/155334

Actions (login required)

View Item View Item