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International Journal of Applied Research
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ISSN Print: 2394-7500, ISSN Online: 2394-5869, CODEN: IJARPF

TCR (Google Scholar): 4.11, TCR (Crossref): 13, g-index: 90

Peer Reviewed Journal

Vol. 11, Issue 6, Part B (2025)

Predicting mental health conditions using social media data

Predicting mental health conditions using social media data

Author(s)
Mahesh and Divya Jatain
Abstract
One of the recognized mental illnesses that affect people is known as Post-Traumatic Stress Disorder (PTSD), it is clearly defined as medical disorder that development precisely after an person has gone through an incredibly traumatic event. Aside from relying on interviews, the pressing question is how do we target the root of the problem without wasting time. It is this gap that has resulted in the relatively new field of analyzing human nature through the use of social media instead of traditional methods. The papers intend to use NLP and ML as tools to analyze and quantify interpersonal posting on social platforms as a way of suffering from PTSD and to offer possible solutions to said condition. The study also reviews existing literature in the field of social media analysis to weigh the negative side of purposive campaigning and social academic discussion. The research emphasizes PTSD combat through social media and the methods that can achieve aforementioned goal. In recent years social media has become the norm in these situations as sharing peoples thoughts is important for early detection. Early detection on a large scale outcome leads to more efficient treatment plans that minimize risk.
Pages: 94-98  |  172 Views  46 Downloads


International Journal of Applied Research
How to cite this article:
Mahesh, Divya Jatain. Predicting mental health conditions using social media data. Int J Appl Res 2025;11(6):94-98. DOI: 10.22271/allresearch.2025.v11.i6b.12639
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