This paper is in the following e-collection/theme issue:

Natural Language Processing (636) Information Seeking, Information Needs (419) Machine Learning (1370) Obesity and Nutrition as Public Health Problem (277) Clinical Informatics (904)

Published on in Vol 10, No 2 (2022): February

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/34492, first published .
Traditional Machine Learning Models and Bidirectional Encoder Representations From Transformer (BERT)–Based Automatic Classification of Tweets About Eating Disorders: Algorithm Development and Validation Study

Traditional Machine Learning Models and Bidirectional Encoder Representations From Transformer (BERT)–Based Automatic Classification of Tweets About Eating Disorders: Algorithm Development and Validation Study

Traditional Machine Learning Models and Bidirectional Encoder Representations From Transformer (BERT)–Based Automatic Classification of Tweets About Eating Disorders: Algorithm Development and Validation Study

Authors of this article:

José Alberto Benítez-Andrades1 Author Orcid Image ;   José-Manuel Alija-Pérez2 Author Orcid Image ;   Maria-Esther Vidal3 Author Orcid Image ;   Rafael Pastor-Vargas4 Author Orcid Image ;   María Teresa García-Ordás2 Author Orcid Image
Article Authors Cited by (18) Tweetations (15) Metrics

José Alberto Benítez-Andrades   1 * , BSc, MSc, PhD ;   José-Manuel Alija-Pérez   2 , BSc, MSc, PhD ;   Maria-Esther Vidal   3 * , BSc, MSc, PhD ;   Rafael Pastor-Vargas   4 * , BSc, MSc, PhD ;   María Teresa García-Ordás   2 * , BSc, MSc, PhD

1 SALBIS Research Group, Department of Electric, Systems and Automatics Engineering, University of León, León, Spain

2 SECOMUCI Research Group, Escuela de Ingenierías Industrial e Informática, Universidad de León, León, Spain

3 Leibniz University of Hannover, Hannover, Germany

4 Communications and Control Systems Department, Spanish National University for Distance Education, Madrid, Spain

*these authors contributed equally

Corresponding Author:

  • José Alberto Benítez-Andrades, BSc, MSc, PhD
  • SALBIS Research Group
  • Department of Electric, Systems and Automatics Engineering
  • University of León
  • Campus of Vegazana s/n
  • León, 24071
  • Spain
  • Phone: 34 987293628
  • Email: jbena@unileon.es