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

Anabel Pineda-Briseño; Josimar Chire-Saire; Jimy Frank Oblitas

doi:10.1007/978-3-032-18293-7_1

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

Anabel Pineda-Briseño
, Josimar Chire-Saire
, Jimy Frank Oblitas

Universidade de São Paulo

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

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.

Original language	English
Title of host publication	Applied Machine Learning and Data Analytics - 7th International Conference, AMLDA 2024, Revised Selected Papers
Editors	Sanju Tiwari, Tasneem Bano, M.A. Jabbar, Fernando Ortiz-Rodriguez, Azanzi Jiomekong
Pages	1-15
Number of pages	15
DOIs	https://doi.org/10.1007/978-3-032-18293-7_1
State	Published - 2026
Event	7th International Conference on Applied Machine Learning and Data Analytics, AMLDA 2024 - Shamshabad, India Duration: 20 Dec 2024 → 21 Dec 2024

Publication series

Name	Communications in Computer and Information Science
Volume	2636 CCIS
ISSN (Print)	1865-0929
ISSN (Electronic)	1865-0937

Conference

Conference	7th International Conference on Applied Machine Learning and Data Analytics, AMLDA 2024
Country/Territory	India
City	Shamshabad
Period	20/12/24 → 21/12/24

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

Keywords

Argentina
COVID-19
Natural Language Processing
Public Health
Sentiment Analysis
Social Media
Topic Modeling

Access to Document

10.1007/978-3-032-18293-7_1

Cite this

Pineda-Briseño, A., Chire-Saire, J., & Oblitas, J. F. (2026). Analyzing COVID-19 Discourse on Twitter in Argentina: Trends, Sentiments, and Key Themes. In S. Tiwari, T. Bano, M. A. Jabbar, F. Ortiz-Rodriguez, & A. Jiomekong (Eds.), Applied Machine Learning and Data Analytics - 7th International Conference, AMLDA 2024, Revised Selected Papers (pp. 1-15). (Communications in Computer and Information Science; Vol. 2636 CCIS). https://doi.org/10.1007/978-3-032-18293-7_1

Pineda-Briseño, Anabel ; Chire-Saire, Josimar ; Oblitas, Jimy Frank. / Analyzing COVID-19 Discourse on Twitter in Argentina : Trends, Sentiments, and Key Themes. Applied Machine Learning and Data Analytics - 7th International Conference, AMLDA 2024, Revised Selected Papers. editor / Sanju Tiwari ; Tasneem Bano ; M.A. Jabbar ; Fernando Ortiz-Rodriguez ; Azanzi Jiomekong. 2026. pp. 1-15 (Communications in Computer and Information Science).

@inproceedings{820ad4da926349d5b52c9f1339f1cfbb,

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

abstract = "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{\textquoteright}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{\textquoteright}s role in crisis management and offers valuable lessons for future health emergencies.",

keywords = "Argentina, COVID-19, Natural Language Processing, Public Health, Sentiment Analysis, Social Media, Topic Modeling",

author = "Anabel Pineda-Brise{\~n}o and Josimar Chire-Saire and Oblitas, \{Jimy Frank\}",

note = "Publisher Copyright: {\textcopyright} The Author(s), under exclusive license to Springer Nature Switzerland AG 2026.; 7th International Conference on Applied Machine Learning and Data Analytics, AMLDA 2024 ; Conference date: 20-12-2024 Through 21-12-2024",

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language = "English",

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editor = "Sanju Tiwari and Tasneem Bano and M.A. Jabbar and Fernando Ortiz-Rodriguez and Azanzi Jiomekong",

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}

Pineda-Briseño, A, Chire-Saire, J & Oblitas, JF 2026, Analyzing COVID-19 Discourse on Twitter in Argentina: Trends, Sentiments, and Key Themes. in S Tiwari, T Bano, MA Jabbar, F Ortiz-Rodriguez & A Jiomekong (eds), Applied Machine Learning and Data Analytics - 7th International Conference, AMLDA 2024, Revised Selected Papers. Communications in Computer and Information Science, vol. 2636 CCIS, pp. 1-15, 7th International Conference on Applied Machine Learning and Data Analytics, AMLDA 2024, Shamshabad, India, 20/12/24. https://doi.org/10.1007/978-3-032-18293-7_1

Analyzing COVID-19 Discourse on Twitter in Argentina: Trends, Sentiments, and Key Themes. / Pineda-Briseño, Anabel; Chire-Saire, Josimar; Oblitas, Jimy Frank.
Applied Machine Learning and Data Analytics - 7th International Conference, AMLDA 2024, Revised Selected Papers. ed. / Sanju Tiwari; Tasneem Bano; M.A. Jabbar; Fernando Ortiz-Rodriguez; Azanzi Jiomekong. 2026. p. 1-15 (Communications in Computer and Information Science; Vol. 2636 CCIS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Analyzing COVID-19 Discourse on Twitter in Argentina

T2 - 7th International Conference on Applied Machine Learning and Data Analytics, AMLDA 2024

AU - Pineda-Briseño, Anabel

AU - Chire-Saire, Josimar

AU - Oblitas, Jimy Frank

N1 - Publisher Copyright: © The Author(s), under exclusive license to Springer Nature Switzerland AG 2026.

PY - 2026

Y1 - 2026

N2 - 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.

AB - 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.

KW - Argentina

KW - COVID-19

KW - Natural Language Processing

KW - Public Health

KW - Sentiment Analysis

KW - Social Media

KW - Topic Modeling

UR - https://www.scopus.com/pages/publications/105031906283

U2 - 10.1007/978-3-032-18293-7_1

DO - 10.1007/978-3-032-18293-7_1

M3 - Conference contribution

AN - SCOPUS:105031906283

SN - 9783032182920

T3 - Communications in Computer and Information Science

SP - 1

EP - 15

BT - Applied Machine Learning and Data Analytics - 7th International Conference, AMLDA 2024, Revised Selected Papers

A2 - Tiwari, Sanju

A2 - Bano, Tasneem

A2 - Jabbar, M.A.

A2 - Ortiz-Rodriguez, Fernando

A2 - Jiomekong, Azanzi

Y2 - 20 December 2024 through 21 December 2024

ER -

Pineda-Briseño A, Chire-Saire J, Oblitas JF. Analyzing COVID-19 Discourse on Twitter in Argentina: Trends, Sentiments, and Key Themes. In Tiwari S, Bano T, Jabbar MA, Ortiz-Rodriguez F, Jiomekong A, editors, Applied Machine Learning and Data Analytics - 7th International Conference, AMLDA 2024, Revised Selected Papers. 2026. p. 1-15. (Communications in Computer and Information Science). doi: 10.1007/978-3-032-18293-7_1

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

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

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