Deep learning based mental health/status interpretation

Detecting mental health disorders through analysis of social media activity is a challenging yet crucial task, particularly in terms of early intervention for individuals experiencing mental health issues. This study introduces an approach to interpreting mental health conditions by employing Deep L...

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Main Author: Teo, Guang Xiang
Other Authors: Vidya Sudarshan
Format: Final Year Project
Language:English
Published: Nanyang Technological University 2023
Subjects:
Online Access:https://hdl.handle.net/10356/171965
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1719652023-11-24T15:38:14Z Deep learning based mental health/status interpretation Teo, Guang Xiang Vidya Sudarshan School of Computer Science and Engineering vidya.sudarshan@ntu.edu.sg Engineering::Computer science and engineering Detecting mental health disorders through analysis of social media activity is a challenging yet crucial task, particularly in terms of early intervention for individuals experiencing mental health issues. This study introduces an approach to interpreting mental health conditions by employing Deep Learning models on Reddit posts. The research utilized deep learning models to examine and classify posts that are associated with mental health disorders. The primary dataset consisted of Reddit posts, with a specific focus on identifying posts related to depression. Moreover, the dataset was also utilized to categorize posts pertaining to various other mental disorders. The study implemented a two-stage classifier to facilitate effective analysis. The initial stage involved filtering out posts that were not relevant to mental disorders, while the subsequent stage focused on categorizing the remaining posts into specific mental disorders. This innovative two- stage approach offers a fresh perspective on utilizing social media data for mental health analysis and has the potential to make significant contributions to the field of digital mental health. Bachelor of Engineering (Computer Engineering) 2023-11-20T00:14:09Z 2023-11-20T00:14:09Z 2023 Final Year Project (FYP) Teo, G. X. (2023). Deep learning based mental health/status interpretation. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/171965 https://hdl.handle.net/10356/171965 en SCSE22-1073 application/pdf Nanyang Technological University
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Engineering::Computer science and engineering
spellingShingle Engineering::Computer science and engineering
Teo, Guang Xiang
Deep learning based mental health/status interpretation
description Detecting mental health disorders through analysis of social media activity is a challenging yet crucial task, particularly in terms of early intervention for individuals experiencing mental health issues. This study introduces an approach to interpreting mental health conditions by employing Deep Learning models on Reddit posts. The research utilized deep learning models to examine and classify posts that are associated with mental health disorders. The primary dataset consisted of Reddit posts, with a specific focus on identifying posts related to depression. Moreover, the dataset was also utilized to categorize posts pertaining to various other mental disorders. The study implemented a two-stage classifier to facilitate effective analysis. The initial stage involved filtering out posts that were not relevant to mental disorders, while the subsequent stage focused on categorizing the remaining posts into specific mental disorders. This innovative two- stage approach offers a fresh perspective on utilizing social media data for mental health analysis and has the potential to make significant contributions to the field of digital mental health.
author2 Vidya Sudarshan
author_facet Vidya Sudarshan
Teo, Guang Xiang
format Final Year Project
author Teo, Guang Xiang
author_sort Teo, Guang Xiang
title Deep learning based mental health/status interpretation
title_short Deep learning based mental health/status interpretation
title_full Deep learning based mental health/status interpretation
title_fullStr Deep learning based mental health/status interpretation
title_full_unstemmed Deep learning based mental health/status interpretation
title_sort deep learning based mental health/status interpretation
publisher Nanyang Technological University
publishDate 2023
url https://hdl.handle.net/10356/171965
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