Abstract
The COVID-19 pandemic is a global crisis that has been testing every society and exposing the critical role of local politics in crisis response. In the United States, there has been a strong partisan divide between the Democratic and Republican party’s narratives about the pandemic which resulted in polarization of individual behaviors and divergent policy adoption across regions. As shown in this case, as well as in most major social issues, strongly polarized narrative frameworks facilitate such narratives. To understand polarization and other social chasms, it is critical to dissect these diverging narratives. Here, taking the Democratic and Republican political social media posts about the pandemic as a case study, we demonstrate that a combination of computational methods can provide useful insights into the different contexts, framing, and characters and relationships that construct their narrative frameworks which individual posts source from. Leveraging a dataset of tweets from the politicians in the U.S., including the ex-president, members of Congress, and state governors, we found that the Democrats’ narrative tends to be more concerned with the pandemic as well as financial and social support, while the Republicans discuss more about other political entities such as China. We then perform an automatic framing analysis to characterize the ways in which they frame their narratives, where we found that the Democrats emphasize the government’s role in responding to the pandemic, and the Republicans emphasize the roles of individuals and support for small businesses. Finally, we present a semantic role analysis that uncovers the important characters and relationships in their narratives as well as how they facilitate a membership categorization process. Our findings concretely expose the gaps in the “elusive consensus” between the two parties. Our methodologies may be applied to computationally study narratives in various domains.
Highlights
Human beings make sense of the reality around them by constructing narratives using what they see, hear, and encounter [49]
Our approach has two key differences from Tangherlini et al [55] in that (i) we consider the context as the main topics and issues that each party engages with, instead of characterizing it with relationships. (ii) we examine framing separately as we consider it to be a central piece of political discourse, which shapes how political narratives are conveyed to the audience independent from what is communicated
We find that the Democratic tweets have over-represented words related to media, such as “telephone”, “town hall”, and “facebook”, while a similar cluster for the Republican tweets appear to be related to the White House and its press conferences, such as “whitehouse” and “press”
Summary
Human beings make sense of the reality around them by constructing narratives using what they see, hear, and encounter [49]. One of the areas where contrasting narratives fiercely collide and fight is politics. In the age of social media, narratives can be circulated, mutated, and amplified with incredible intensity and speed [4, 15]. The anti-mask and anti-vaccine narratives, accompanied by conspiracy theories, fake news, and unverified anecdotes, discouraged mask usage and vaccination heavily, which might have led to the loss of hundreds of thousands more lives [56]. Such narratives often lead to collisions between partisan beliefs that strengthen political polarization [52]. As can be seen in the case of the pandemic narratives, understanding social conflicts and polarization is often impossible without understanding diverging narratives
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
