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Authors: John Paul S. Guzman 1 ; Charibeth Cheng 2 ; Jan Michael Alexandre C. Bernadas 3 and Angelyn Lao 1

Affiliations: 1 Department of Mathematics and Statistics, De La Salle University, Manila, Philippines ; 2 Department of Software Technology, De La Salle University, Manila, Philippines ; 3 Department of Communication, De La Salle University, Manila, Philippines

Keyword(s): Aspect-Based Sentiment Analysis, Twitter, COVID-19.

Abstract: During the COVID-19 pandemic, X (formerly known as Twitter) was teeming with rich discussions as people shared their experiences and concerns. Understanding the sentiments in these tweets could aid in gauging public reactions and enhancing public health communication. While some studies analyze public health sentiments, few specifically focus on aspect-level sentiments in the Global South. In this study, we examine tweets published in the Philippines during the COVID-19 pandemic and aspects relevant to the pandemic. The sentiment polarities of tweet-aspect pairs are annotated. We analyze these pairs to understand the sentiments expressed during this period. These insights can improve health communication in the Philippines by assessing public receptiveness to policies, monitoring events that influence sentiment, and identifying communication gaps. Notably, we observed disproportionately high amounts of negative sentiment toward the Sinopharm and Sinovac vaccines. This sentiment indic ates distrust and racial bias against Chinese brands. Moreover, the consistent negative sentiment toward face shields over an extended period highlights shortcomings in health communication about their effectiveness. (More)

CC BY-NC-ND 4.0

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Paper citation in several formats:
Guzman, J. P. S., Cheng, C., Bernadas, J. M. A. C. and Lao, A. (2025). Aspect-Level Sentiment Analysis of Filipino Tweets During the COVID-19 Pandemic. In Proceedings of the 18th International Joint Conference on Biomedical Engineering Systems and Technologies - HEALTHINF; ISBN 978-989-758-731-3; ISSN 2184-4305, SciTePress, pages 343-350. DOI: 10.5220/0013053100003911

@conference{healthinf25,
author={John Paul S. Guzman and Charibeth Cheng and Jan Michael Alexandre C. Bernadas and Angelyn Lao},
title={Aspect-Level Sentiment Analysis of Filipino Tweets During the COVID-19 Pandemic},
booktitle={Proceedings of the 18th International Joint Conference on Biomedical Engineering Systems and Technologies - HEALTHINF},
year={2025},
pages={343-350},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013053100003911},
isbn={978-989-758-731-3},
issn={2184-4305},
}

TY - CONF

JO - Proceedings of the 18th International Joint Conference on Biomedical Engineering Systems and Technologies - HEALTHINF
TI - Aspect-Level Sentiment Analysis of Filipino Tweets During the COVID-19 Pandemic
SN - 978-989-758-731-3
IS - 2184-4305
AU - Guzman, J.
AU - Cheng, C.
AU - Bernadas, J.
AU - Lao, A.
PY - 2025
SP - 343
EP - 350
DO - 10.5220/0013053100003911
PB - SciTePress