Sentiment Analysis of Tweets on Coronavirus Disease 2019 (COVID-19) Pandemic from Metro Manila, Philippines
Published Online: Dec 10, 2020
Page range: 141 - 155
Received: Mar 17, 2020
Accepted: Oct 07, 2020
DOI: https://doi.org/10.2478/cait-2020-0052
Keywords
© 2020 Manuel B. Garcia, published by Sciendo
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
From the outbreak of a novel COronaVIrus Disease (COVID-19) in Wuhan to the first COVID-19 case in the Philippines, Filipinos have been enthusiastically engaging on Twitter to convey their sentiments. As such, this paper aims to identify the public opinion of Filipino twitter users concerning COVID-19 in three different timelines. Toward this goal, a total of 65,396 tweets related to COVID-19 were sent to data analysis using R Statistical Software. Results show that “mask”, “health”, “lockdown”, “outbreak”, “test”, “kit”, “university”, “alcohol”, and “suspension” were some of the most frequently occurring words in the tweets. The study further investigates Filipinos’ emotions regarding COVID-19 by calculating text polarity of the dataset. To date, this is the first paper to perform sentiment analysis on tweets pertaining to COVID-19 not only in the Filipino context but worldwide as well.