Early Detection of Mental Health over Social Media Using Machine Learning

Simple item page
creativework.keywordsMental Health, Social Media, Machine Learning
dc.contributor.advisorMd. Shahriar Karim
dc.contributor.authorSabbir Hasan
dc.contributor.authorMd. Tashfiq H. Choudhury
dc.contributor.id1411107042
dc.contributor.id1611508042
dc.coverage.departmentElectrical and Computer Engineering
dc.date.accessioned2025-04-16
dc.date.accessioned2025-04-16T09:19:28Z
dc.date.available2025-04-16T09:19:28Z
dc.date.issued2020
dc.description.abstractIn this project, we have worked on the use of machine learning algorithms that may indicate the mental state or sentiment of the users of social media. The current linguistic research on tweets or statuses shows distinct language patterns talks much about the sentiments of the users. As such, we are encouraged to use the available social media dataset repository for performance analysis of the supervised learning models generally applied in the case of large datasets. We have captured the texts and preprocessed the text data using Python tools for feature selection that provides clues to sentiment and subsequently, the subjective sentences are classified as positive or negative. We built machine learning (ML) models out of the classified text features for random forest and LSTM algorithms. The accuracy of the classification in both cases is encouraging, particularly the LSTM algorithm. The whole work is carried out using rich libraries of Python machine language modules. A prototype web application is developed with a front end (input and output) and back end (ML models and classification) using a rapid prototype web application framework for testing the algorithms that enable us to check the mental status of a social media user to determine if they may require medical or emotional support. Social media emerges as the most critical source of information, reflecting people's expressions and communication through textual content. This work contributes to the application of machine learning to further enhance the early detection of the mental health of users.
dc.description.degreeUndergraduate
dc.identifier.cdTo be determined
dc.identifier.print-thesis600000594
dc.identifier.urihttps://repository.northsouth.edu/handle/123456789/1114
dc.language.isoen
dc.publisherNorth South University
dc.rights©NSU Library
dc.titleEarly Detection of Mental Health over Social Media Using Machine Learning
dc.typeThesis
oaire.citation.endPage37
oaire.citation.startPage1
Files
Original bundle
Now showing 1 - 2 of 2
Thumbnail Image
Name:
600000594.Abstract.pdf
Size:
158 KB
Format:
Adobe Portable Document Format
Description:
Download
Thumbnail Image
Name:
600000594.pdf
Size:
1.05 MB
Format:
Adobe Portable Document Format
Description:
Download
License bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
license.txt
Size:
1.93 KB
Format:
Item-specific license agreed to upon submission
Description:
Download
Collections
Theses - Undergraduate