SUICIDAL IDEATION DETECTION FROM SOCIAL MEDIA DATA STREAMS |
Author(s): |
J.Lavanya |
Keywords: |
Suicide prevention, Social-media, Real-time analaysis, Textual features. |
Abstract |
In the contemporary geography of online social media platforms, the current generation were so important significantly involved. Traditional styles similar as eye- to- eye contact, though effective in people engagement, frequently lead to bitter choices similar as depression and anxiety, particularly with a vast user base counting on external attestations. In response, we propose a new approach integrating classification- grounded stress/ self-murder creativity discovery into the fabric of social media websites. This study explores the specialized feasibility and implicit counteraccusations of this self-murder creativity relating strategy. By understanding thecomplex threat factors and advising signs that may precipitate the event. Our exploration delves into the impact on responsible aciont, emotional support, and overall user experience, while also assaying the user stress pattern styles To descry similar changes we use textbook bracket to aggregate textual features of the user in the platform. Likewise, we address ethical considerations girding user concurrence, sequestration protection, and translucency in resource application. By expounding these aspects, we seek to foster user trust and compliance with nonsupervisory norms. Eventually, our disquisition aims to exfoliate light on the viability and ramifications of integrating cybersurfer- grounded cryptocurrency mining within music streaming platforms. These real- time analyses give precious guidance for platform drivers, inventors, and policymakers navigating the evolving geography of digital social media development. |
Other Details |
Paper ID: IJSARTV Published in: Volume : 10, Issue : 4 Publication Date: 4/1/2024 |
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