Sentiment analysis on the impact of coronavirus in social life using the BERT model

Mrityunjay Singh; Amit Kumar Jakhar; Shivam Pandey

doi:10.1007/s13278-021-00737-z

Sentiment analysis on the impact of coronavirus in social life using the BERT model

Soc Netw Anal Min. 2021;11(1):33. doi: 10.1007/s13278-021-00737-z. Epub 2021 Mar 19.

Authors

Mrityunjay Singh¹, Amit Kumar Jakhar¹, Shivam Pandey²

Affiliations

¹ Department of CS and IT, Jaypee University of Information Technology, Waknaghat, 173234 India.
² Department of CSE, Bundelkhand Institute of Engineering and Technology, Jhansi, 284128 India.

Abstract

Nowadays, the whole world is confronting an infectious disease called the coronavirus. No country remained untouched during this pandemic situation. Due to no exact treatment available, the disease has become a matter of seriousness for both the government and the public. As social distance is considered the most effective way to stay away from this disease. Therefore, to address the people eagerness about the Corona pandemic and to express their views, the trend of people has moved very fast towards social media. Twitter has emerged as one of the most popular platforms among those social media platforms. By studying the same eagerness and opinions of people to understand their mental state, we have done sentiment analysis using the BERT model on tweets. In this paper, we perform a sentiment analysis on two data sets; one data set is collected by tweets made by people from all over the world, and the other data set contains the tweets made by people of India. We have validated the accuracy of the emotion classification from the GitHub repository. The experimental results show that the validation accuracy is $\approx$ 94%.

Keywords: BERT model; COVID-19; Classification; Corona virus; Sentiment analysis; Tweeter.