Coronavirus Pandemic (COVID-19)

TLDR

Social media, especially Twitter, has become a platform where people openly express fear and other emotions about COVID‑19. The study aims to analyze the sentiment of English tweets to assess how COVID‑19 influences public emotions across ten identified themes. Researchers applied natural‑language processing, textual analysis, computational linguistics, and biometric techniques to a large Twitter dataset to extract and classify emotional content. Results show COVID‑19 spreads fear and anxiety while also eliciting gratitude, happiness, and hope; positive chloroquine news temporarily reduced fear and boosted positive emotions, but FDA’s warning reversed this effect.

Abstract

People are afraid about COVID-19 and are actively talking about it on social media platforms such as Twitter. People are showing their emotions openly in their tweets on Twitter. It's very important to perform sentiment analysis on these tweets for finding COVID-19's impact on people's lives. Natural language processing, textual processing, computational linguists, and biometrics are applied to perform sentiment analysis to identify and extract the emotions. In this work, sentiment analysis is carried out on a large Twitter dataset of English tweets. Ten emotional themes are investigated. Experimental results show that COVID-19 has spread fear/anxiety, gratitude, happiness and hope, and other mixed emotions among people for different reasons. Specifically, it is observed that positive news from top officials like Trump of chloroquine as cure to COVID-19 has suddenly lowered fear in sentiment, and happiness, gratitude, and hope started to rise. But, once FDA said, chloroquine is not effective cure, fear again started to rise.