Public Sentiment Analysis on Twitter Data during COVID-19 Outbreak

The COVID-19 pandemic, is also known as the coronavirus pandemic, is an ongoing serious global problem all over the world. The outbreak first came to light in December 2019 in Wuhan, China. This was declared pandemic by the World Health Organization on 11th March 2020. COVID-19 virus infected on people and killed hundreds of thousands of people in the United States, Brazil, Russia, India and several other countries. Since this pandemic continues to affect millions of lives, and a number of countries have resorted to either partial or full lockdown. People took social media platforms to share their emotions, and opinions during this lockdown to find a way to relax and calm down. In this research work, sentiment analysis on the tweets of people from top ten infected countries has been conducted. The experiments have been conducted on the collected data related to the tweets of people from top ten infected countries with the addition of one more country chosen from Gulf region, i.e. Sultanate of Oman. A dataset of more than 50,000 tweets with hashtags like #covid-19, #COVID19, #CORONAVIRUS, #CORONA, #StayHomeStaySafe, #Stay Home, #Covid_19, #CovidPandemic, #covid19, #Corona Virus, #Lockdown, #Qurantine, #qurantine, #Coronavirus Outbreak, #COVID etc. posted between June 21, 2020 till July 20, 2020 was considered in this research. Based on the tweets posted in English a sentiment analysis was performed. This research was conducted to understand how people from different infected countries cope with the situation. The tweets were collected, pre-processed and then text mining algorithms used and finally sentiment analysis have been done and presented with the results. The purpose of this research paper to know about the sentiments of people from COVID-19 infected countries.

@article{Kausar2021,
  title     = {Public Sentiment Analysis on Twitter Data during COVID-19 Outbreak},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {12},
  number    = {2},
  year      = {2021},
  publisher = {The Science and Information Organization},
  author    = {Mohammad Abu Kausar and Arockiasamy Soosaimanickam and Mohammad Nasar},
  doi       = {10.14569/IJACSA.2021.0120252},
  url       = {https://doi.org/10.14569/IJACSA.2021.0120252}
}