A Study on Sentiment Analysis of Mental Illness Using Machine Learning Techniques

Author:

Tiwari Pradeep Kumar,Sharma Muskan,Garg Payal,Jain Tarun,Verma Vivek Kumar,Hussain Afzal

Abstract

Abstract In the digital age, social media plays a crucial role in society. Social media provides a platform to youth for exchanging their views on public issues and express their personal issues. Hence online media can be used for studying the behavior of people. Applying sentiment analysis on the data obtained timely from social networking sites (here Twitter), depression, anorexia, and other similar mental illness can be predicted among youth. The importance of detecting depression is that it is the root cause of a plethora of diseases. Early prediction can also mitigate the number of suicides. This work is to detect depression and PTSD (Post Traumatic Stress Disorder) among the Twitter users. Analysing the tweets, how likely a person is to suffer from any of the aforementioned diseases can be discovered.

Publisher

IOP Publishing

Subject

General Medicine

Reference12 articles.

1. Recursive deep models for semantic compositionality over a sentiment treebank;Socher,2013

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