Pandemic Messaging: Congressional Communication and the Mechanisms of Polarizing Rhetoric

Abstract

U.S. senators are increasingly turning to Twitter to stoke partisan divisions, and it’s not just what they say, but rather how they say it. Senators spent the Spring of 2020 responding to the COVID-19 pandemic, but the tone and framing used to engage a digital constituency was largely dependent on partisan alignment with President Trump. We use senators’ Twitter activity during the outbreak to offer new insight into the mechanisms of lawmakers’ party polarizing trends in congressional communication. We show that divisions stemmed from senators’ sentiment and framing—with Republicans more likely to incorporate positivity into forward-looking steps for economic recovery and Democrats preferring a negative tone to address government failings and inadequate response by President Trump. This article extends the literature on polarizing rhetoric in the Senate by using the pandemic response to illustrate how the dynamics of senators’ digital rhetoric, even during a moment of shared crisis, continue to fuel partisanship and polarizing narratives.

Acknowledgments

We thank Nathan Walter and comments at the 2019 National Communication Association Conference, and Jenifer Whitten-Woodring and comments at the 2019 APSA Political Communication Pre-Conference for helpful comments on earlier drafts. All errors remain the authors’ responsibility.

Disclosure statement

The authors report there are no competing interests to declare.

Notes

1 Early studies of social media and politics have analyzed Twitter as a mechanism for spreading information and seeking support (Bennett and Segerberg 2013; Jungherr and Jürgens 2013; Papacharissi and de Fatima Oliveira 2012; Poell and Borra 2012; Tufekci and Wilson 2012). Congressional Twitter studies have addressed politicians’ adoption of Twitter (Chi and Yang 2010; Lassen and Brown 2011; Peterson 2012; Straus et al. 2013), and how Twitter has become a normalized communication tool in Congress (Evans et al. 2017; Gelman 2019; Gervais and Morris 2018; Russell 2018a, 2021).

2 Defined by Russell (2018a), this rhetoric generally includes positive overtones that signal favoritism or support for one’s own party, such as promoting the party’s candidates in upcoming elections, promoting party-specific legislation, or emphasizing positive party performance.

3 A complete list of COVID-related words for dictionary is included in the Appendix.

4 Examples of both positive and negative words, and specifically Covid-related messaging, are included in the Appendix.

5 Race is not included in the model due to a lack of significance and minimal racial diversity in the Senate.

6 Examples of positive and negative words included in the Appendix

7 The coefficient on Republican has a point estimate of 0.543, so the ratio is exp(.543) = 0.58 times less than Dems. This means Dems have a negative tweet rate that is 1/exp(.543) = 1.72 times that of Republicans, or 72% more. Alternatively, 1/exp(-.543-1.96*.0716) = 1.98 and 1/exp(-.543 + 1.96*.0716)=1.50, so Democrats have somewhere between a 50% and 98% higher negativity rate.

8 https://twitter.com/ChrisMurphyCT/status/1232312117190987776.