Depression and Stress Monitoring System via Social Media Data using Deep Learning Framework
| Author(s) | : | Paulami Banerjee, Dhanashree A. Phalke |
| Institution | : | Department of Computer Engineering, D.Y. Patil College of Engineering, SPPU, Pune |
| Published In | : | Vol. 7, Issue 7 — July 2020 |
| Page No. | : | 52-57 |
| Domain | : | Engineering |
| Type | : | Research Paper |
| ISSN (Online) | : | 2348-4470 |
| ISSN (Print) | : | 2348-6406 |
Stress and Depression is nowadays are broadly perceived and increasing mental issue that completely influencespresent society. A health monitoring system that works automatically can be of major importance and also be very critical toimprove the sadness and stress recognition framework using social networking site data. The operation of content mining,also the natural language approaches for planning to recognize the feeling or opinion is the function of sentiment analysis.Full of feeling Computing is a way of the examination and advancement of the frameworks and gadgets that can perceive,decipher, process, and mimic the human effects. Sentiment Analysis along with the deep learning techniques could combinedtogether provide us powerful algorithms and frameworks for a given target and observing of mental issues that are,specifically related to depression and stress. In addition, a fundamental plan for incorporating a framework for stress anddepression checking is studied. In particular, the paper traces the basic issues and moves comparative with the structure ofsuch a framework.
Paulami Banerjee, Dhanashree A. Phalke, “Depression and Stress Monitoring System via Social Media Data using Deep Learning Framework”, International Journal of Advance Engineering and Research Development (IJAERD), Vol. 7, Issue 7, pp. 52-57, July 2020.
