Exploring the Sentiments and Emotions in Tweets to Analyze the Impact of Covid-19 Vaccine in the Philippines

Abstract

The Coronavirus disease or COVID-19 is a viral disease caused by SARS-CoV-2, and by March 11, 2020, it was declared a pandemic by the World Health Organization (WHO). The COVID-19 pandemic did not only cause stress due to the illness itself, but it has also brought in severe and complex issues when it comes to quality of life. Passed studies have shown that Twitter was used in public health research, where most focused on evaluating the contents of the tweets. With that being said, during the COVID-19 pandemic, multiple research papers have used Twitter to create datasets pertaining to tweets related to COVID-19. In this study, data from an existing dataset was analyzed. After applying data scraping and identifying the frequencies of concerning variables, the study's main findings show that the most dominant sentiment category from March 2020 to December 2021 was the NEGATIVE category, while the most dominant emotion category was the JOY category. Regarding topics, Topic 1, Topic 2, and Topic 3 were the three most dominant topics throughout the considered time period. Lastly, most of the identified users were Male, and the keyword ‘covid’ was the most used keyword in the gathered tweets.