Abstract
The Covid-19 pandemic has had a negative impact on the physical health of the Central American population. Fear, anxiety and stress were normal reactions in quarantine, due to the uncertainty of the unknown, which makes it understandable that the population experienced feelings or psychological affections. Social networks were the means of communication for thousands of people in quarantine. The increased use of social networks to share comments, content and opinions makes it possible to have a large amount of information. Twitter has been one of the most widely used social networks due to its ease of access and use. The analysis of tweets requires a systematic process for their collection, transformation and classification, integrating different artificial intelligence tools such as natural language processing, automatic learning or deep learning. Automatic text classification aims at finding an adequate way to categorize the documents according to the attributes made up of words that describe each specific category. For this reason, our study has been carried out with a corpus in Spanish extracted from Twitter for the automatic classification of texts, from which we have categorized, through the automatic learning approach, the tweets about Covid-19 in the Central American region, in order to know if the population has suffered any psychological effects. Based on the results, we can say that the automatic learning models provide competitive results in terms of automatic identification of texts with an accuracy of 89%.
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Acknowledgments
The authors would like to thank the National Secretariat of Science, Technology and Innovation of Panama (SENACYT, SNI) for the support given in the development of this research. Also, Panama of the Technological University of Panama (FISC-UTP).
Authors Contribution. Conceptualization DCM; methodology DCM; formal analysis DCM, NN; research DCM; original-writing CM, MVL, NN; writing-review and edition DCM, MVL; Corresponding author DCM.
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Cedeno-Moreno, D., Vargas-Lombardo, M., Navarro, N. (2023). Automatic Classification of Tweets Identifying Mental Health Conditions in Central American Population in a Pandemic. In: Valencia-García, R., Bucaram-Leverone, M., Del Cioppo-Morstadt, J., Vera-Lucio, N., Centanaro-Quiroz, P.H. (eds) Technologies and Innovation. CITI 2023. Communications in Computer and Information Science, vol 1873. Springer, Cham. https://doi.org/10.1007/978-3-031-45682-4_10
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