Automatic determination of the color of the Mexican semaphore of COVID-19 from the news
Keywords:COVID-19, natural language processing, textual classification, epidemiological semaphore
This paper presents the analysis of textual classification models to automatically determine the Mexican regional epidemiological traffic light through COVID news. A database was collected with 4,270 news items referring to COVID, from June 1, 2020, to March 28, 2021. The label of each news item is the color of the epidemiological traffic light that the Mexican government cataloged in the week of publication of the news Classifiers such as SVM, KNN, Random Forest, and Deep Learning were applied. The results show that it is possible to take advantage of the information published in the news to determine the color of the traffic light up to 4 weeks in advance, obtaining results of up to 0.74 F-measure, which is a competitive result taking into account the imbalance of classes of this task.
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Copyright (c) 2022 Miguel Ángel Alvarez-Carmona, Ramón Aranda
This work is licensed under a Creative Commons Attribution 4.0 International License.