Twitter Sentiment Analysis During Covid-19 Outbreak in Nepal

Abstract

The growth of social data on the web is increasing rapidly nowadays. This leads to researchers to access the data and information for the research purpose. During the global COVID-19 outbreak, many individuals as well as organizations and government agencies are posting their viewpoints regarding the coronavirus. The study focuses on the sentiment analysis of tweets of the Twitter social media using Python programming language with Tweepy and TextBlob library. The tweets have been collected, preprocessed and then used for text mining and sentiment analysis using Google Colab. The graphical representation has been provided on the data after sentiment analysis based on two specified hashtags keywords : #COVID-19 and #coronavirus. The data are collected from the users who shared their location as ‘Nepal’ between 21st May 2020 and 31st May 2020. The result of the study concluded that while majority of the people of Nepal are taking a positive and hopeful approach, there are instances of fear, sadness and disgust exhibited too.

Keywords: COVID-19, coronavirus, TextBlob, Tweepy, Sentiment Analysis, Twitter