| Abstrakt: |
In today's world, most of us use social media sites such as Fb, Twitter, YouTube and many more to connect with each other. Addiction to social media, can make you feel quite lonely and isolated and exacerbate mental disorders such as anxiety and depression. The number of people affected by mental illness is increasing, on the costs of medical management and public health, lost productivity, and quality-adjusted life years. Social media users frequently express their emotions or feelings in their posts. In this study, we developed classification models to determine a user's state of mind based on his or her posting data. We assembled posts from Reddit's mental disorders societies to that end. By evaluating and learning stuff written by users, our proposed system could correctly determine if a user's post focuses on a specific mental illness, such as depression, anxiety, or addiction. Based on their content, we assume our model can aid in the identification of potential sufferers of mental illness. We also provide a word cloud analysis for a higher level comparison for the key words indifferent potential mental illness and normal posts.This study also describe the implication of our developed framework that can be used as a supplement to moniter mental disorder who frequently use digital platforms. [ABSTRACT FROM AUTHOR] |
