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Analyzing COVID-19 Discourse on Twitter in Argentina: Trends, Sentiments, and Key Themes

  • Universidade de São Paulo

Producción científica: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva

Resumen

In the era of the COVID-19 pandemic, social media platforms have become essential conduits for disseminating information. Twitter, with its real-time nature and global reach, has played a pivotal role in facilitating this dynamic. This research paper delves into the multi-faceted landscape of Twitter conversations surrounding the pandemic in Argentina from its onset in 2020 through 2023. Utilizing advanced Natural Language Processing (NLP) and sentiment analysis techniques, we examine the emotional tone and evolving topics of discussion among the Argentine Twitter community. Our findings reveal significant trends in public sentiment and highlight key moments that influenced the discourse. By analyzing over 1.2 million Spanish-language tweets, this study provides insights into the public’s reaction to major epidemiological events, government interventions, and societal changes. The results underscore the importance of social media as a barometer for public opinion and its impact on public health communication strategies. This work contributes to the broader understanding of social media’s role in crisis management and offers valuable lessons for future health emergencies.

Idioma originalInglés
Título de la publicación alojadaApplied Machine Learning and Data Analytics - 7th International Conference, AMLDA 2024, Revised Selected Papers
EditoresSanju Tiwari, Tasneem Bano, M.A. Jabbar, Fernando Ortiz-Rodriguez, Azanzi Jiomekong
Páginas1-15
Número de páginas15
DOI
EstadoPublicada - 2026
Evento7th International Conference on Applied Machine Learning and Data Analytics, AMLDA 2024 - Shamshabad, India
Duración: 20 dic. 202421 dic. 2024

Serie de la publicación

NombreCommunications in Computer and Information Science
Volumen2636 CCIS
ISSN (versión impresa)1865-0929
ISSN (versión digital)1865-0937

Conferencia

Conferencia7th International Conference on Applied Machine Learning and Data Analytics, AMLDA 2024
País/TerritorioIndia
CiudadShamshabad
Período20/12/2421/12/24

ODS de las Naciones Unidas

Este resultado contribuye a los siguientes Objetivos de Desarrollo Sostenible

  1. ODS 3: Salud y bienestar
    ODS 3: Salud y bienestar

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