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