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

M. Samonte, Alexandra Mikaela G. Celestial
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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.
探索推文中的情绪和情绪,分析Covid-19疫苗对菲律宾的影响
冠状病毒病或COVID-19是由SARS-CoV-2引起的病毒性疾病,到2020年3月11日,它被世界卫生组织(WHO)宣布为大流行。COVID-19大流行不仅因疾病本身而造成压力,而且在生活质量方面也带来了严重而复杂的问题。过去的研究表明,Twitter被用于公共卫生研究,其中大多数集中在评估推文的内容。话虽如此,在COVID-19大流行期间,多篇研究论文使用Twitter创建了与COVID-19相关的推文数据集。在本研究中,分析了来自现有数据集的数据。在应用数据抓取和识别相关变量的频率后,该研究的主要发现表明,从2020年3月到2021年12月,最主要的情绪类别是消极类别,而最主要的情绪类别是快乐类别。关于话题,话题1、话题2和话题3是整个研究期间最主要的三个话题。最后,大多数确定的用户是男性,关键字“covid”是收集的推文中使用最多的关键字。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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