Sentiment analysis of the NIGERIAN nationwide lockdown due to COVID19 outbreak

Abstract

Sentiment analysis is a classification technique that specializes in categorizing a body of texts into various emotions. This categorization had proven to be handy in classifying tweets into positive, negative, or neutral emotions. Nigerians had been on a nationwide lockdown due to COVID19 since 30th March 2020. The analysis of the emotions of Nigerians during this period is expedient to understand the effectiveness of exercise and the impact it has on the masses. The focus of this paper is to determine the sentiment analysis of Nigerians within the period of the lockdown exercise. Using a lexicon-based analytic architecture and a streaming API to TwitterNG, we extracted a total of 22, 249 tweets from the timelines of national stakeholders on COVID19 and location-based tweets from the general public. The tweets were extracted and collated using a set of ten hashtags/keywords from 30th March to 11th May 2020. The analysis was done in R Programming Software with the application of the NRC lexicon approach to classifying the emotions of Nigerians within the period. The result showed that Nigerians expressed an overall positive sentiment to the lockdown exercise despite a few negative expressions.