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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]

The purpose of this study is to examine mental illness stigma in the college campus context to better understand how public stigma dimensions, specifically, are represented and act as a deterrent to college student mental illness treatment-seeking on campus. We situate our findings in the broader context of stigma research to consider how public stigma dimensions related to mental illness in the college campus context compare to public stigma dimensions found in broader national and international contexts. Using an electronic survey focused on college student perceptions of mental illness and treatment, we collected data from a sample of full-time students enrolled in campus-based programs at a mid-sized regional university during the fall 2018 semester. Findings indicate that the students in our sample hold relatively low levels of endorsement for most commonly endorsed public stigma items related to mental illness but that the public stigma items they endorse reflect the global core of public prejudice associated with mental illness. Specifically, public stigma items reflecting perceptions of dangerousness and treatment carryover have the greatest levels of student endorsement. We also find some differences in endorsement of mental illness public stigma by diagnosis status. Additionally, we find marginal support for the role of exclusionary sentiments on campus mental health helpseeking. These findings suggest universities have potential to serve as an innovative context of change for altering the larger landscape of mental illness stigma through approaches taken for addressing stigma on campus, keeping in mind well-known forms of structural stigma that concurrently hinder student access to mental illness treatment. [ABSTRACT FROM AUTHOR]