Covid-19 Discourse on Twitter: How the Topics, Sentiments, Subjectivity, and Figurative Frames Changed Over Time

TL;DR

This study analyzes Twitter discourse during the first wave of COVID-19, revealing how topics, sentiments, subjectivity, and figurative frames evolved over time in response to pandemic developments.

Contribution

It provides an extensive temporal analysis of COVID-19 related Twitter discourse, highlighting changes in topics, sentiment, subjectivity, and figurative language during the pandemic's first wave.

Findings

Topics shifted over time with pandemic development

Sentiment became more negative during reopening phases

Subjectivity increased linearly over time

Abstract

The words we use to talk about the current epidemiological crisis on social media can inform us on how we are conceptualizing the pandemic and how we are reacting to its development. This paper provides an extensive explorative analysis of how the discourse about Covid-19 reported on Twitter changes through time, focusing on the first wave of this pandemic. Based on an extensive corpus of tweets (produced between 20th March and 1st July 2020) first we show how the topics associated with the development of the pandemic changed through time, using topic modeling. Second, we show how the sentiment polarity of the language used in the tweets changed from a relatively positive valence during the first lockdown, toward a more negative valence in correspondence with the reopening. Third we show how the average subjectivity of the tweets increased linearly and fourth, how the popular and frequently used figurative frame of WAR changed when real riots and fights entered the discourse.