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Analyzing Spanish-Language Public Sentiment in the Context of a Pandemic and Social Unrest: The Panama Case

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  • Fernando Arias

    (Research Group on Advanced Technologies of Telecommunications and Signal Processing (GITTS), Faculty of Electrical Engineering, Technological University of Panama, Panama City 0819-07289, Panama
    Centro de Estudios Multidisciplinarios en Ciencias, Ingeniería y Tecnología AIP (CEMCIT-AIP), Technological University of Panama, Panama City 0819-07289, Panama
    Centro de Investigación e Innovación Eléctrica, Mecánica y de la Industria (CINEMI), Technological University of Panama, Panama City 0819-07289, Panama
    These authors contributed equally to this work.)

  • Ariel Guerra-Adames

    (Research Group on Advanced Technologies of Telecommunications and Signal Processing (GITTS), Faculty of Electrical Engineering, Technological University of Panama, Panama City 0819-07289, Panama
    Centro de Estudios Multidisciplinarios en Ciencias, Ingeniería y Tecnología AIP (CEMCIT-AIP), Technological University of Panama, Panama City 0819-07289, Panama
    These authors contributed equally to this work.)

  • Maytee Zambrano

    (Research Group on Advanced Technologies of Telecommunications and Signal Processing (GITTS), Faculty of Electrical Engineering, Technological University of Panama, Panama City 0819-07289, Panama
    Centro de Estudios Multidisciplinarios en Ciencias, Ingeniería y Tecnología AIP (CEMCIT-AIP), Technological University of Panama, Panama City 0819-07289, Panama)

  • Efraín Quintero-Guerra

    (Research Group on Advanced Technologies of Telecommunications and Signal Processing (GITTS), Faculty of Electrical Engineering, Technological University of Panama, Panama City 0819-07289, Panama)

  • Nathalia Tejedor-Flores

    (Centro de Estudios Multidisciplinarios en Ciencias, Ingeniería y Tecnología AIP (CEMCIT-AIP), Technological University of Panama, Panama City 0819-07289, Panama
    Centro de Investigaciones Hidráulicas e Hidrotécnicas (CIHH), Technological University of Panama, Panama City 0819-07289, Panama)

Abstract

Over the past decade, an increase in global connectivity and social media users has changed the way in which opinions and sentiments are shared. Platforms such as Twitter can act as public forums for expressing opinions on non-personal matters, but often also as an outlet for individuals to share their feelings and personal thoughts. This becomes especially evident during times of crisis, such as a massive civil disorder or a pandemic. This study proposes the estimation and analysis of sentiments expressed by Twitter users of the Republic of Panama during the years 2019 and 2020. The proposed workflow is comprised of the extraction, quantification, processing and analysis of Spanish-language Twitter data based on Sentiment Analysis. This case of study highlights the importance of developing natural language processing resources explicitly devised for supporting opinion mining applications in Latin American countries, where language regionalisms can drastically change the lexicon on each country. A comparative analysis performed between popular machine learning algorithms demonstrated that a version of a distributed gradient boosting algorithm could infer sentiment polarity contained in Spanish text in an accurate and time-effective manner. This algorithm is the tool used to analyze over 20 million tweets produced between the years of 2019 and 2020 by residents of the Republic of Panama, accurately displaying strong sentiment responses to events occurred in the country over the two years that the analysis performed spanned. The obtained results highlight the potential that methodologies such as the one proposed in this study could have for transparent government monitoring of responses to public policies on a population scale.

Suggested Citation

  • Fernando Arias & Ariel Guerra-Adames & Maytee Zambrano & Efraín Quintero-Guerra & Nathalia Tejedor-Flores, 2022. "Analyzing Spanish-Language Public Sentiment in the Context of a Pandemic and Social Unrest: The Panama Case," IJERPH, MDPI, vol. 19(16), pages 1-19, August.
    • Handle: RePEc:gam:jijerp:v:19:y:2022:i:16:p:10328-:d:892552
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    References listed on IDEAS

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    1. Md Shoaib Ahmed & Tanjim Taharat Aurpa & Md Musfique Anwar, 2021. "Detecting sentiment dynamics and clusters of Twitter users for trending topics in COVID-19 pandemic," PLOS ONE, Public Library of Science, vol. 16(8), pages 1-20, August.
    2. Carol Shofiya & Samina Abidi, 2021. "Sentiment Analysis on COVID-19-Related Social Distancing in Canada Using Twitter Data," IJERPH, MDPI, vol. 18(11), pages 1-10, June.
    3. Gabriela Fernandez & Carol Maione & Harrison Yang & Karenina Zaballa & Norbert Bonnici & Jarai Carter & Brian H. Spitzberg & Chanwoo Jin & Ming-Hsiang Tsou, 2022. "Social Network Analysis of COVID-19 Sentiments: 10 Metropolitan Cities in Italy," IJERPH, MDPI, vol. 19(13), pages 1-31, June.
    4. David A Broniatowski & Michael J Paul & Mark Dredze, 2013. "National and Local Influenza Surveillance through Twitter: An Analysis of the 2012-2013 Influenza Epidemic," PLOS ONE, Public Library of Science, vol. 8(12), pages 1-1, December.
    5. Dimitrios Kydros & Maria Argyropoulou & Vasiliki Vrana, 2021. "A Content and Sentiment Analysis of Greek Tweets during the Pandemic," Sustainability, MDPI, vol. 13(11), pages 1-21, May.
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    1. Solange Parra-Soto & Samuel Duran-Aguero & Francisco Vargas-Silva & Katherine Vázquez-Morales & Rafael Pizarro-Mena, 2023. "Social Outbreak in Chile, and Its Association with the Effects Biological, Psychological, Social, and Quality of Life," IJERPH, MDPI, vol. 20(23), pages 1-17, November.

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