@inproceedings{pachon-etal-2021-identification,
title = "Identification of profession {\&} occupation in Health-related Social Media using tweets in {S}panish",
author = "Pach{\'o}n, Victoria and
Mata V{\'a}zquez, Jacinto and
Dom{\'\i}nguez Olmedo, Juan Lu{\'\i}s",
editor = "Magge, Arjun and
Klein, Ari and
Miranda-Escalada, Antonio and
Al-garadi, Mohammed Ali and
Alimova, Ilseyar and
Miftahutdinov, Zulfat and
Farre-Maduell, Eulalia and
Lopez, Salvador Lima and
Flores, Ivan and
O'Connor, Karen and
Weissenbacher, Davy and
Tutubalina, Elena and
Sarker, Abeed and
Banda, Juan M and
Krallinger, Martin and
Gonzalez-Hernandez, Graciela",
booktitle = "Proceedings of the Sixth Social Media Mining for Health ({\#}SMM4H) Workshop and Shared Task",
month = jun,
year = "2021",
address = "Mexico City, Mexico",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2021.smm4h-1.20",
doi = "10.18653/v1/2021.smm4h-1.20",
pages = "105--107",
abstract = "In this paper we present our approach and system description on Task 7a in ProfNer-ST: Identification of profession {\&} occupation in Health related Social Media. Our main contribution is to show the effectiveness of using BETO-Spanish BERT as a model based on transformers pretrained with a Spanish Corpus for classification tasks. In our experiments we compared several architectures based on transformers with others based on classical machine learning algorithms. With this approach, we achieved an F1-score of 0.92 in the evaluation process.",
}
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%0 Conference Proceedings
%T Identification of profession & occupation in Health-related Social Media using tweets in Spanish
%A Pachón, Victoria
%A Mata Vázquez, Jacinto
%A Domínguez Olmedo, Juan Luís
%Y Magge, Arjun
%Y Klein, Ari
%Y Miranda-Escalada, Antonio
%Y Al-garadi, Mohammed Ali
%Y Alimova, Ilseyar
%Y Miftahutdinov, Zulfat
%Y Farre-Maduell, Eulalia
%Y Lopez, Salvador Lima
%Y Flores, Ivan
%Y O’Connor, Karen
%Y Weissenbacher, Davy
%Y Tutubalina, Elena
%Y Sarker, Abeed
%Y Banda, Juan M.
%Y Krallinger, Martin
%Y Gonzalez-Hernandez, Graciela
%S Proceedings of the Sixth Social Media Mining for Health (#SMM4H) Workshop and Shared Task
%D 2021
%8 June
%I Association for Computational Linguistics
%C Mexico City, Mexico
%F pachon-etal-2021-identification
%X In this paper we present our approach and system description on Task 7a in ProfNer-ST: Identification of profession & occupation in Health related Social Media. Our main contribution is to show the effectiveness of using BETO-Spanish BERT as a model based on transformers pretrained with a Spanish Corpus for classification tasks. In our experiments we compared several architectures based on transformers with others based on classical machine learning algorithms. With this approach, we achieved an F1-score of 0.92 in the evaluation process.
%R 10.18653/v1/2021.smm4h-1.20
%U https://aclanthology.org/2021.smm4h-1.20
%U https://doi.org/10.18653/v1/2021.smm4h-1.20
%P 105-107
Markdown (Informal)
[Identification of profession & occupation in Health-related Social Media using tweets in Spanish](https://aclanthology.org/2021.smm4h-1.20) (Pachón et al., SMM4H 2021)
ACL