A comparative analysis of machine learning, deep learning, and ensemble learning models for suicidal ideation detection on social media
- DOI
- 10.1371/journal.pmen.0000721
- Published
- 2026-10-22
- Container
- PLOS Mental Health
- Publisher
- Public Library of Science (PLoS)
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1371/journal.pmen.0000721,
title = {A comparative analysis of machine learning, deep learning, and ensemble learning models for suicidal ideation detection on social media},
author = {Andualem Woldegiorgis and Mohammed Abebe and Durga Prasad Sharma and Worku Jimma},
year = {2026},
journal = {PLOS Mental Health},
doi = {10.1371/journal.pmen.0000721},
url = {https://doi.org/10.1371/journal.pmen.0000721}
}RIS
TY - JOUR TI - A comparative analysis of machine learning, deep learning, and ensemble learning models for suicidal ideation detection on social media AU - Andualem Woldegiorgis AU - Mohammed Abebe AU - Durga Prasad Sharma AU - Worku Jimma PY - 2026 JO - PLOS Mental Health DO - 10.1371/journal.pmen.0000721 UR - https://doi.org/10.1371/journal.pmen.0000721 ER -
APA
Woldegiorgis, A., Abebe, M., Sharma, D. P., & Jimma, W. (2026). A comparative analysis of machine learning, deep learning, and ensemble learning models for suicidal ideation detection on social media. PLOS Mental Health. https://doi.org/10.1371/journal.pmen.0000721
Source records
- crossref · retrieved 2026-11-10T19:09:40.072Z