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

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

*Corresponding author for this work

    Research output: Contribution to journalArticlepeer-review

    49 Citations (Scopus)

    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.

    Original languageEnglish
    Pages (from-to)3751-3756
    Number of pages6
    JournalInternational Journal of Electrical and Computer Engineering
    Volume10
    Issue number4
    DOIs
    Publication statusPublished - 01-01-2020

    All Science Journal Classification (ASJC) codes

    • General Computer Science
    • Electrical and Electronic Engineering

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