Redirigiendo al acceso original de articulo en 18 segundos...
Inicio  /  Information  /  Vol: 12 Par: 5 (2021)  /  Artículo
ARTÍCULO
TITULO

Twitter Sentiment Analysis towards COVID-19 Vaccines in the Philippines Using Naïve Bayes

Charlyn Villavicencio    
Julio Jerison Macrohon    
X. Alphonse Inbaraj    
Jyh-Horng Jeng and Jer-Guang Hsieh    

Resumen

A year into the COVID-19 pandemic and one of the longest recorded lockdowns in the world, the Philippines received its first delivery of COVID-19 vaccines on 1 March 2021 through WHO?s COVAX initiative. A month into inoculation of all frontline health professionals and other priority groups, the authors of this study gathered data on the sentiment of Filipinos regarding the Philippine government?s efforts using the social networking site Twitter. Natural language processing techniques were applied to understand the general sentiment, which can help the government in analyzing their response. The sentiments were annotated and trained using the Naïve Bayes model to classify English and Filipino language tweets into positive, neutral, and negative polarities through the RapidMiner data science software. The results yielded an 81.77% accuracy, which outweighs the accuracy of recent sentiment analysis studies using Twitter data from the Philippines.

 Artículos similares

       
 
Nirmalya Thakur    
This paper presents multiple novel findings from a comprehensive analysis of a dataset comprising 1,244,051 Tweets about Long COVID, posted on Twitter between 25 May 2020 and 31 January 2023. First, the analysis shows that the average number of Tweets pe... ver más

 
Paraskevas Koukaras, Dimitrios Rousidis and Christos Tjortjis    
The identification and analysis of sentiment polarity in microblog data has drawn increased attention. Researchers and practitioners attempt to extract knowledge by evaluating public sentiment in response to global events. This study aimed to evaluate pu... ver más
Revista: Informatics

 
Josip Katalinic, Ivan Dunder and Sanja Seljan    
Politically polarizing issues are a growing concern around the world, creating divisions along ideological lines, which was also confirmed during the 2022 United States midterm elections. The purpose of this study was to explore the relationship between ... ver más
Revista: Information

 
Xu Chen, Zihe Wang and Xuan Di    
This paper aims to leverage Twitter data to understand travel mode choices during the pandemic. Tweets related to different travel modes in New York City (NYC) are fetched from Twitter in the two most recent years (January 2020?January 2022). Building on... ver más
Revista: Information

 
Nirmalya Thakur, Yuvraj Nihal Duggal and Zihui Liu    
In the last decade and a half, the world has experienced outbreaks of a range of viruses such as COVID-19, H1N1, flu, Ebola, Zika virus, Middle East Respiratory Syndrome (MERS), measles, and West Nile virus, just to name a few. During these virus outbrea... ver más
Revista: Computers