SENTIMENT ANALYSIS FOR DEPRESSION DETECTION

Abstract

The Covid-19 pandemic has dramatically changed the way we have used to live. The pandemic has been causing significant devastations in economy, and health, inter alia. Mental health, especially, has become a growing concern due to employment terminations, income loss, family stress and other uncertainties. The pandemic disproportionally affected mental health of younger population. Nowadays risk of early death is increasing due to mental illness which is mostly caused due to depression. Depression creates suicidal thoughts causing serious impairments in daily life. Sentiment analysis is a hot topic that’s been on research for decades, which intends to find the nature of text and classifies into positive, negative and neutral. In today’s digital world lot of data can be made available for sentiment analysis. Hence, our aim is to focus on creating a depression detection system from text, video & audio analysis. Sentiment Analysis and Natural Language Processing methods will be used to develop this system. The system will classify text, audio and video cues as positive or negative depending on the emotions inferred from user’s input.