Análisis de sentimiento de tweets sobre la vacuna contra el COVID-19 en países iberoamericanos hispanohablantes
Sentiment analysis of tweets about the COVID-19 vaccine in Spanish-speaking Ibero-American countries
Pedro Antonio Salcedo Lagos
,
Gabriela Emilce Kotz Grabole
,
Carla Michele Vergara Espinoza
,
Miguel Enrique Sánchez-Hechavarría
Revista Latinoamericana de Psicología, (2022), 54, pp. 1-11.
Recibido el 11 de julio de 2021
Aceptado el 7 de febrero de 2022
Introducción: En este estudio se evalúa la emocionalidad asociada a la vacunación contra el COVID-19 a partir de la técnica de análisis de sentimientos de los tweets en países iberoamericanos hispanohablantes. Método: En enero de 2021 se realizó un estudio mixto observacional transversal de 41023 tweets procedentes de nueve países iberoamericanos hispanohablantes (Chile, El Salvador, Venezuela, Ecuador, Argentina, México, Panamá, Perú y España) con una fase cuantitativa y técnicas de análisis de sentimientos mediante algoritmos de inteligencia artificial y una fase cualitativa donde se realizó un análisis del discurso de los tweets cuya emocionalidad era en extremo positiva y negativa. Resultados: A partir del análisis de sentimiento de los tweets, se observó que los países presentan una emocionalidad negativa asociada a la vacunación contra el COVID-19, que se podría atribuir a la desconfianza hacia las autoridades y a la eficacia o seguridad de las vacunas, según el análisis del discurso en los tweets de emocionalidad en extremo negativa. Conclusiones: Las técnicas de análisis de sentimientos en combinación con el análisis del discurso de la emocionalidad extrema posibilitaron la monitorización de las opiniones negativas y sus posibles factores asociados en la vacunación contra el COVID-19 en los países iberoamericanos estudiados.
Palabras clave:
Vacunación, COVID-19, análisis de sentimientos, inteligencia artificial, Twitter, análisis del discurso
Introduction: This study evaluates the emotionality associated with vaccination against COVID-19 using the sentiment analysis technique of tweets in Spanish-speaking Ibero-American countries. Method: In January 2021 a mixed cross-sectional observational study of 41023 tweets from nine Spanish-speaking Ibero-American countries (Chile, El Salvador, Venezuela, Ecuador, Argentina, Mexico, Panama, Peru and Spain) was carried out with a quantitative phase and analysis techniques of feelings based on artificial intelligence algorithms and a qualitative phase where an analysis of the discourse of the tweets whose emotionality was extremely positive and negative was carried out. Results: From the sentiment analysis of the tweets, it was observed that the countries present a negative emotionality associated with the vaccination against COVID-19, which could be attributed to mistrust towards the authorities and the efficacy or safety of the vaccines, according to the analysis of the discourse in the extremely negative emotionality tweets. Conclusions: Sentiment analysis techniques in combination with extreme emotionality discourse analysis made it possible to monitor negative opinions and their possible associated factors in vaccination against COVID-19 in the Ibero-American countries studied.
Keywords:
Vaccination, COVID-19, sentiment analysis, artificial intelligence, Twitter, discourse analysis
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