ISSN (Online) : 2456 - 0774

Email : ijasret@gmail.com

ISSN (Online) 2456 - 0774

TWITTER BASED DEPRESSION DETECTOR TO DETECTWHETHER A PERSON IS IN DEPRESSION BY FOLLOWINGHIS/HER TWEETS

Abstract

Abstract: Tension might be seen as a disturbance in a state of natural psychological equilibrium. When a person is unable toreconcile the expectations placed on him or her with his or her ability to deal with them, tension arises, putting a strain onmental health. There are two distinct types of challenges. Depression can be defined as a disturbance in one's psychologicalhomeostasis. Depression detection is one of the primary research subjects in biomedical engineering, as proper depressionprevention might be simple. Mri, Rgb, oxygenation, Frs, and other bio signals are provided. These signals are effective indetermining depression levels because they show unique variations in the induction of depression. Because of the ease withwhich they can be recorded, we chose Twitter tweets as the main contenders for our project.Multiple SVM model types havebeen checked by changing the function number and kernel type 

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