The Conversation around COVID-19 on Twitter—Sentiment Analysis and Topic Modelling to Analyse Tweets Published in English during the First Wave of the Pandemic

Abstract

The COVID-19 pandemic disrupted societies all over the world. In an interconnected and digital global society, social media was the platform not only to convey information and recommendations but also to discuss the pandemic and its consequences. Focusing on the phase of stabilization during the first wave of the pandemic in Western countries, this work analyses the conversation around it through tweets in English. For that purpose, the authors have studied who the most active and influential accounts were, identified the most frequent words in the sample, conducted topic modelling, and researched the predominant sentiments. It was observed that the conversation followed two main lines: a more political and controversial one, which can be exemplified by the relevant presence of former US President Donald Trump, and a more informational one, mostly concerning recommendations to fight the virus, represented by the World Health Organization. In general, sentiments were predominantly neutral due to the abundance of information.

Keywords

• COVID-19
• coronavirus
• pandemic
• Twitter
• topic modelling
• sentiment analysis