TY - JOUR
T1 - Predicting depression using deep learning and ensemble algorithms on raw twitter data
AU - Shetty, Nisha P.
AU - Muniyal, Balachandra
AU - Anand, Arshia
AU - Kumar, Sushant
AU - Prabhu, Sushant
N1 - Publisher Copyright:
Copyright © 2020 Institute of Advanced Engineering and Science. All rights reserved.
PY - 2020/1/1
Y1 - 2020/1/1
N2 - 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.
AB - 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.
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U2 - 10.11591/ijece.v10i4.pp3751-3756
DO - 10.11591/ijece.v10i4.pp3751-3756
M3 - Article
AN - SCOPUS:85079880542
SN - 2088-8708
VL - 10
SP - 3751
EP - 3756
JO - International Journal of Electrical and Computer Engineering
JF - International Journal of Electrical and Computer Engineering
IS - 4
ER -