Sentiment Analysis of Filipinos and Effects of Extreme Community Quarantine Due to Coronavirus (COVID-19) Pandemic

Abstract

The start of the Extreme Community Quarantine in the Philippines last March 2020 became the intervention of the government to slow down the spread of the coronavirus or more commonly known as COVID-19. The Pandemic was interfering many operations in the world which brought challenges to all affected countries which includes the Philippines. This study aims to reveal the sentiment of the Filipinos in the effect of extreme community quarantine caused by COVID-19 Pandemic particularly Luzon. It aims to gather the tweets of Twitter users in the Philippines in Luzon areas. This research also analyzes the effect of extreme community quarantine and other effects of the Pandemic to personal lifestyle based on the tweets of the users. Natural Language Processing is one of the methodologies to determine the sentiment of users from extracted tweets. Opinions are treated as data for analyzation. A qualitative approach was also used in determining the effects of the extreme community quarantine in the Luzon area. The sentiment reveals that most of the Filipinos encountered several problems concerning extreme community quarantine. The general sentiment shows that one basic needs are affected regarding the food supply and support from the government. It is concluded that most of the twitter users in Luzon have negative sentiment over COVID-19, while some users are speaking about the positive effects, it was miscredited to the coronavirus instead of crediting to the decision such as community quarantine, lockdown and social distancing. It is concluded that negative sentiments increase over time, and it is expected that negative sentiments among twitter users increases. It is recommended that intervention should be done based on the requirement of the Filipinos who encounter problem in the food shortage and everyone should support to flatten the curve in order for the operations and life back to normal. This study also aims to provide recommendations in the future.

Keywords: Sentiment Analysis, Coronavirus, COVID-19 Pandemic