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 language | English |
|---|---|
| Pages (from-to) | 3751-3756 |
| Number of pages | 6 |
| Journal | International Journal of Electrical and Computer Engineering |
| Volume | 10 |
| Issue number | 4 |
| DOIs | |
| Publication status | Published - 01-01-2020 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
All Science Journal Classification (ASJC) codes
- General Computer Science
- Electrical and Electronic Engineering
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