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

Nisha P. Shetty, Balachandra Muniyal, Arshia Anand, Sushant Kumar, Sushant Prabhu

Research output: Contribution to journalArticlepeer-review

25 Citations (Scopus)


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.

Original languageEnglish
Pages (from-to)3751-3756
Number of pages6
JournalInternational Journal of Electrical and Computer Engineering
Issue number4
Publication statusPublished - 01-01-2020

All Science Journal Classification (ASJC) codes

  • Computer Science(all)
  • Electrical and Electronic Engineering


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