AI To Detect Social Media Users Depression Polarity Score and Diagnose Using Auto Curative Therapy

AI To Detect Social Media Users Depression Polarity Score and Diagnose Using Auto Curative Therapy
Author(s):
R.Danush Vikram, K.S.Sudhishna, M.Lingeshraj, N.Gokulswaruban
Keywords:
SVM, KNN, Decision Tree, and Ensemble Learning have all been used in a few related studies. Some studies use a single set of features to identify depression in their posts, such as bag of words (BOW), N-grams, LIWC, or LDA.
Abstract
Depression is regarded as a major cause of global impairment and a leading cause of suicide. People are increasingly using social media to communicate their emotions these days. Sentiment Analysis (SA) is a computational tool for examining the polarity of emotions and ideas expressed in a text. We hope to forecast depressed individuals and quantify their depression intensity using social media (Twitter) data in this study, which will aid in sounding an alarm.
Article Details
Unique Paper ID: 154942 Publication Volume & Issue: Volume 8, Issue 12 Page(s): 1646 - 1649
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