Research on Sentimental Analysis on Mental Health Using Social Media

This project investigates the use of machine learning and natural language processing techniques in sentiment analysis of mental health discussions on social media platforms. By employing both traditional methods and advanced deep learning models such as LSTM and BERT, the study aims to achieve precise sentiment classification. The insights gained are intended to support mental health advocacy and strategy development. Future work will focus on improving model robustness and incorporating multi-modal data for enhanced sentiment detection

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-03-01
DOI
https://doi.org/10.5281/zenodo.14954477
Primary Topic
Mental Health via Writing
Type
article
Field-Weighted Citation Impact
0.00
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article

Research on Sentimental Analysis on Mental Health Using Social Media

Zenodo (CERN European Organization for Nuclear Research)
Mental Health via Writing
article

Research on Sentimental Analysis on Mental Health Using Social Media

article en

Abstract

This project investigates the use of machine learning and natural language processing techniques in sentiment analysis of mental health discussions on social media platforms. By employing both traditional methods and advanced deep learning models such as LSTM and BERT, the study aims to achieve precise sentiment classification. The insights gained are intended to support mental health advocacy and strategy development. Future work will focus on improving model robustness and incorporating multi-modal data for enhanced sentiment detection

Zenodo (CERN European Organization for Nuclear Research)
Quality Education
Openalex Percentile: Top 47%
Mental Health via Writing
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Research on Sentimental Analysis on Mental Health Using Social Media · Zenodo (CERN European Organization for Nuclear Research) (2025) | TGRS Research Map | TGRS