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Personality and Its Partisan Political Correlates Predict U.S. State Differences in Covid-19 Policies and Mask Wearing Percentages.

ABSTRACT: A central feature of the Covid-19 pandemic is state differences. Some state Governors closed all but essential businesses, others did not. In some states, most of the population wore face coverings when in public; in other states, <50% wore face coverings. According to journalists, these differences were symptomatic of a politically polarized America. The Big 5 personality factors also cluster at the state level. For example, residents of Utah score high on Conscientiousness and low on Neuroticism, whereas residents of Massachusetts and Connecticut show the opposite pattern. In state-level regressions that controlled for partisan political allegiances, Conscientiousness was a significant (negative) predictor of the stringency of state Covid-19 restrictions, whereas Openness was a significant (positive) predictor of mask wearing. A number of the predictors were strongly correlated with each other. For example, the correlation coefficient linking Openness with the percentage of Democratic state legislators was r = 0.53. Commonality regression partitions the explained variance between the amount that is unique to each predictor and the amount that is shared among subsets of correlated predictors. This approach revealed that the common variance shared by Conscientiousness, Openness and partisan politics accounted for 34% of the state differences in Covid-19 policy and 35% of the state differences in mask wearing. The results reflect the importance of personality in how Americans have responded to the Covid-19 pandemic.

SUBMITTER: Heyman GM

PROVIDER: S-EPMC8502796 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description: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.Supplementary informationThe online version contains supplementary material available at 10.1140/epjds/s13688-021-00308-4.

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Personality and Its Partisan Political Correlates Predict U.S. State Differences in Covid-19 Policies and Mask Wearing Percentages.

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