Traditional Machine Learning Models and Bidirectional Encoder Representations From Transformer (BERT)–Based Automatic Classification of Tweets About Eating Disorders: Algorithm Development and Validation Study
- DOI
- 10.2196/34492
- Published
- 2022-02-24
- Container
- JMIR Medical Informatics
- Publisher
- JMIR Publications Inc.
- Open access
- unknown
Credibility signals
uncertain Score 64/100 under policy 1.0.0. This is a metadata assessment, not a judgment of the paper's conclusions.
Show all credibility signals
- supportingDOI registered: A matching record was returned by Crossref.
- supportingDOI resolves: A matching record was returned by Crossref.
- not scoredDirectory of Open Access Journals: No matching DOAJ record was present in this response. No allow-list match; this is not evidence of low credibility.
- not scoredMEDLINE indexed: Not checked or no result supplied; no credibility inference made.
- not scoredOpenAlex core source: Not checked or no result supplied; no credibility inference made.
- not scoredKnown publisher allow-list: Not checked or no result supplied; no credibility inference made.
- not scoredROR affiliation: Not checked or no result supplied; no credibility inference made.
- not scoredRetraction Watch retraction: No retraction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete.
- not scoredRetraction Watch expression of concern: No expression of concern notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete.
- not scoredRetraction Watch correction: No correction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete.
- not scoredRetraction Watch reinstatement: No reinstatement notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete.
- not scoredOpen access status: Not checked or no result supplied; no credibility inference made.
- not scoredPublication license: Not checked or no result supplied; no credibility inference made.
- not scoredPublication version: A publication version was supplied but is not scored.
- supportingMetadata completeness: All 6 scored descriptive metadata groups are present.
Cite this work
BibTeX
@article{allodium:10.2196/34492,
title = {Traditional Machine Learning Models and Bidirectional Encoder Representations From Transformer (BERT)–Based Automatic Classification of Tweets About Eating Disorders: Algorithm Development and Validation Study},
author = {José Alberto Benítez-Andrades and José-Manuel Alija-Pérez and Maria-Esther Vidal and Rafael Pastor-Vargas and María Teresa García-Ordás},
year = {2022},
journal = {JMIR Medical Informatics},
doi = {10.2196/34492},
url = {https://doi.org/10.2196/34492}
}RIS
TY - JOUR TI - Traditional Machine Learning Models and Bidirectional Encoder Representations From Transformer (BERT)–Based Automatic Classification of Tweets About Eating Disorders: Algorithm Development and Validation Study AU - José Alberto Benítez-Andrades AU - José-Manuel Alija-Pérez AU - Maria-Esther Vidal AU - Rafael Pastor-Vargas AU - María Teresa García-Ordás PY - 2022 JO - JMIR Medical Informatics DO - 10.2196/34492 UR - https://doi.org/10.2196/34492 ER -
APA
Benítez-Andrades, J. A., Alija-Pérez, J., Vidal, M., Pastor-Vargas, R., & García-Ordás, M. T. (2022). Traditional Machine Learning Models and Bidirectional Encoder Representations From Transformer (BERT)–Based Automatic Classification of Tweets About Eating Disorders: Algorithm Development and Validation Study. JMIR Medical Informatics. https://doi.org/10.2196/34492
Source records
- crossref · retrieved 2026-09-25T00:25:59.254Z