Red Media vs. Blue Media: Social Distancing and Partisan News Media Use during the COVID-19 Pandemic

References

• Aaro, D. (2020). What are the levels of severity for coronavirus and how does pneumonia impact the body? https://www.foxnews.com/health/what-are-levels-severity-covid-19-how-does-pneumonia-impact-body
   Google Scholar
• Allassan, F. (2020, September 28). Fauci: Some of what Fox News reports about COVID-19 is “outlandish”. AXIOS. https://www.axios.com/fauci-fox-news-covid-outlandish-79d9a7d2-bae2-476e-b0be-205bb923dc05.html
   Google Scholar
• Barlett, D. L., Drew, P. B., Fahle, E. G., & Watts, W. A. (1974). Selective exposure to a presidential campaign appeal. Public Opinion Quarterly, 38(2), 264–270. https://doi.org/10.1086/268158
   Web of Science ®Google Scholar
• Baum, M. A. (2011). Red state, blue state, flu state: Media self-selection and partisan gaps in swine flu vaccinations. Journal of Health Politics, Policy and Law, 36(6), 1021–1059. https://doi.org/10.1215/03616878-1460569
   PubMed Web of Science ®Google Scholar
• Bennett, W. L., & Iyengar, S. (2008). A new era of minimal effects? The changing foundations of political communication. The Journal of Communication, 58(4), 707–731. https://doi.org/10.1111/j.1460-2466.2008.00410.x
   Web of Science ®Google Scholar
• Borah, P. (2011). Conceptual issues in framing theory: A systematic examination of a decade’s literature. The Journal of Communication, 61(2), 246–263. https://doi.org/10.1111/j.1460-2466.2011.01539.x
   Web of Science ®Google Scholar
• Borah, P. (2022). Message framing and COVID-19 vaccination intention: Moderating roles of partisan media use and pre-attitudes about vaccination. Current Psychology, 1–10. https://doi.org/10.1007/s12144-022-02851-3
   PubMed Web of Science ®Google Scholar
• Bowden, J. (2020, February 25). Limbaugh claims coronavirus is being ‘weaponized’ to ‘bring down’ Trump. The Hill. https://thehill.com/homenews/media/484506-limbaugh-claims-coronavirus-is-being-weaponized-to-bring-down-trump
   Google Scholar
• Butterfuss, R., Aubele, J., & Kendeou, P. (2020). Hedged language and partisan media influence belief in science claims. Science Communication, 42(2), 147–171. https://doi.org/10.1177/1075547020908598
   Web of Science ®Google Scholar
• Chan, M. P. S., Jones, C. R., Hall Jamieson, K., & Albarracín, D. (2017). Debunking: A meta-analysis of the psychological efficacy of messages countering misinformation. Psychological Science, 28(11), 1531–1546. https://doi.org/10.1177/0956797617714579
   PubMed Web of Science ®Google Scholar
• Church, M. (2020, March 19). Coronavirus ‘lockdowns’ are ultimately assaults on freedom. Daily Caller. https://dailycaller.com/2020/03/19/church-coronavirus-lockdowns-are-ultimately-assaults-on-freedom/
   Google Scholar
• Ciaccia, C. (2020, April 14). If China acted earlier, coronavirus cases could have been cut by as much as 95 percent: Former FDA chief. Fox News. https://www.foxnews.com/science/if-china-had-acted-earlier-coronavirus-cases-could-have-been-cut-by-as-much-as-95-percent-study-says
   Google Scholar
• Cochrane, E., & Fandos, N. (2020, May 24). Democrats near deal with White House on stimulus package. The New York Times. https://www.nytimes.com/2020/03/24/us/politics/coronavirus-stimulus-bill.html
   Google Scholar
• Cotton, J. (1985). Cognitive dissonance in selective exposure. In D. Zillmann & J. Bryant (Eds.), Selective exposure to communication (pp. 11–33). Routledge.
   Google Scholar
• Dong, E., Du, H., & Gardner, L. (2020). An interactive web-based dashboard to track COVID-19 in real time. The Lancet Infectious Diseases, 20(5), 533–534. https://doi.org/10.1016/S1473-30992030120-1
   PubMed Web of Science ®Google Scholar
• Druckman, J. (2001). The implications of framing effects for citizen competence. Political Behavior, 23(3), 225–256. https://doi.org/10.1023/A:1015006907312
   Web of Science ®Google Scholar
• Dunwoody, S. (2014). Science journalism. In M. Bucchi & B. Trench (Eds.), Routledge handbook of public communication of science and technology (pp. 27–39). Routledge.
   Google Scholar
• Dylko, I. B. (2016). How technology encourages political selective exposure. Communication Theory, 26(4), 389–409. https://doi.org/10.1111/comt.12089
   Web of Science ®Google Scholar
• Edelman, M. (1993). Contestable categories and public opinion. Political Communication, 10(3), 231–242. https://doi.org/10.1080/10584609.1993.9962981
   Google Scholar
• Entman, R. (1991). Framing United States coverage of international news: Contrasts in narratives of the Kal and Iran air incidents. The Journal of Communication, 41(4), 6–27. https://doi.org/10.1111/j.1460-2466.1991.tb02328.x
   Web of Science ®Google Scholar
• Faris, R., Roberts, H., Etling, B., Bourassa, N., Zuckerman, E., & Benkler, Y. (2017). Partisanship, propaganda, and disinformation: Online media and the 2016 US presidential election. Berkman Klein Center Research Publication, 6. https://ssrn.com/abstract=3019414
   Google Scholar
• Festinger, L. (1957). A theory of cognitive dissonance. Stanford University Press.
   Google Scholar
• Fowler, E. F., & Gollust, S. E. (2015). The content and effect of politicized health controversies. The Annals of the American Academy of Political and Social Science, 658(1), 155–171. https://doi.org/10.1177/0002716214555505
   Web of Science ®Google Scholar
• Freedman, J. L. (1965). Preference for dissonant information. Journal of Personality and Social Psychology, 2(2), 287–289. https://doi.org/10.1037/h0022415
   PubMed Web of Science ®Google Scholar
• Frisby, C. M. (2018). “Oh, See What We Say:” A content analysis of partisan media’s framing of the “take a knee” silent protest by the NFL. American International Journal of Humanities and Social Science, 4(3), 6–18. http://aijhss.cgrd.org/images/Vol4No3/2.pdf
   Google Scholar
• Garrett, R. K., Long, J. A., & Jeong, M. S. (2019). From partisan media to misperception: Affective polarization as mediator. The Journal of Communication, 69(5), 490–512. https://doi.org/10.1093/joc/jqz028
   Web of Science ®Google Scholar
• Glanz, J., & Robertson, C. (2020, May 22). Lockdown delays cost at least 36,000 lives, data show. The New York Times. https://www.nytimes.com/2020/05/20/us/coronavirus-distancing-deaths.html
   Google Scholar
• Goidel, R. K., Shields, T., & Peffley, M. (1997). Priming theory and RAS models: Toward an integrated perspective of media influence. American Politics Quarterly, 25(3), 287–318. https://doi.org/10.1177/1532673X9702500303
   Google Scholar
• Gollwitzer, A., Martel, C., Brady, W. J., Parnamets, P., Freedman, I., Knowles, E., & Bavel, J. (2020). Partisan differences in physical distancing are linked to health outcomes during the COVID-19 pandemic. Nature Human Behavior, 4(11), 1186–1197. https://doi.org/10.1038/s41562-020-00977-7
   PubMed Web of Science ®Google Scholar
• Green, J., Edgerton, J., Naftel, D., Shoub, K., & Cranmer, S. J. (2020). Elusive consensus: Polarization in elite communication on the COVID-19 pandemic. Science Advances, 6(28), eabc2717.
   PubMed Web of Science ®Google Scholar
• Grossman, G., Kim, S., Rexer, J. M., & Thirumurthy, H. (2020). Political partisanship influences behavioral responses to governors’ recommendations for COVID-19 prevention in the United States. Proceedings of the National Academy of Sciences, 117(39), 24144–24153. https://doi.org/10.1073/pnas.2007835117
   PubMed Web of Science ®Google Scholar
• Hart, P. S., & Nisbet, E. C. (2012). Boomerang effects in science communication: How motivated reasoning and identity cues amplify opinion polarization about climate mitigation policies. Communication Research, 39(6), 701–723. https://doi.org/10.1177/0093650211416646
   Web of Science ®Google Scholar
• Iyengar, S. (1991). Is anyone responsible? How television frames political issues. University of Chicago Press.
   Google Scholar
• Iyengar, S., & Hahn, K. S. (2009). Red media, blue media: Evidence of ideological selectivity in media use. The Journal of Communication, 59(1), 19–39. https://doi.org/10.1111/j.1460-2466.2008.01402.x
   Web of Science ®Google Scholar
• Jamieson, K. H., Hardy, B., & Romer, D. (2007). The effectiveness of the press in serving the needs of American democracy. In K. H. Jamieson (Ed.), A republic divided: The Annenberg Democracy Project. Oxford University Press.
   Google Scholar
• Kahan, D. M., Jenkins-Smith, H., & Braman, D. (2011). Cultural cognition of scientific consensus. Journal of Risk Research, 14(2), 147–174. https://doi.org/10.1080/13669877.2010.511246
   Web of Science ®Google Scholar
• Killgore, W. D., Cloonan, S. A., Taylor, E. C., & Dailey, N. S. (2021). The COVID-19 vaccine is here—now who is willing to get it?. Vaccines, 9(4), 339. https://doi.org/10.3390/vaccines9040339
   PubMed Web of Science ®Google Scholar
• Kuhn, K. D. (2018). Using structural topic modeling to identify latent topics and trends in aviation incident reports. Transportation Research Part C: Emerging Technologies, 87, 105–122.
   Web of Science ®Google Scholar
• Kunda, Z. (1990). The case for motivated reasoning. Psychological Bulletin, 108(3), 480–498. https://doi.org/10.1037/0033-2909.108.3.480
   PubMed Web of Science ®Google Scholar
• Lazarsfeld, P. F., Berelson, B., & Gaudet, H. (1948). The people’s choice: How the voter makes up his mind in a presidential campaign. Columbia University Press.
   Google Scholar
• Lee, N. Y. (2020). Partisan online media use, political misinformation, and attitudes toward partisan issues. The Social Science Journal, 1–14. https://doi.org/10.1080/03623319.2020.1728508
   Google Scholar
• Liu, B. F., & Kim, S. (2011). How organizations framed the 2009 H1N1 pandemic via social and traditional media: Implications for US health communicators. Public Relations Review, 37(3), 233–244.
   Web of Science ®Google Scholar
• May, T. (2020). Anti-vaxxers, politicization of science, and the need for trust in pandemic response. Journal of Health Communication, 25(10), 761–763. https://doi.org/10.1080/10810730.2020.1864519
   PubMed Web of Science ®Google Scholar
• Monson, S. (2017). Ebola as African: American media discourses of panic and otherization. Africa Today, 63(3), 3–27. https://doi.org/10.2979/africatoday.63.3.02
   Google Scholar
• Moon, W. K., Atkinson, L., Kahlor, L. A., Yun, C., & Son, H. (2021). U.S. political partisanship and COVID-19: Risk information seeking and prevention behaviors. Health Communication, 37(13), 1671–1681. https://doi.org/10.1080/10410236.2021.1912948
   PubMed Web of Science ®Google Scholar
• Motta, M., Stecula, D., & Farhart, C. (2020). How right-leaning media coverage of COVID-19 facilitated the spread of misinformation in the early stages of the pandemic in the US. Canadian. Journal of Political Science, 53(2), 335–342. https://doi.org/10.1017/S0008423920000396
   Google Scholar
• Nisbet, M. C. (2005). The competition for worldviews: Values, information, and public support for stem cell research. International Journal of Public Opinion Research, 17(1), 90–112. https://doi.org/10.1093/ijpor/edh058
   Web of Science ®Google Scholar
• Nisbet, M. C., & Goidel, R. K. (2007). Understanding citizen perceptions of science controversy: Bridging the ethnographic-survey research divide. Public Understanding of Science, 16(4), 421–440. https://doi.org/10.1177/0963662506065558
   Web of Science ®Google Scholar
• Nivre, J. (2010). Dependency parsing. Language and Linguistics Compass, 4(3), 138–152. https://doi.org/10.1111/j.1749-818X.2010.00187.x
   Google Scholar
• Pollino, J. (2020, April 6). I’m fighting coronavirus on the front lines. And yet I’ve heard the pandemic called a ‘hoax.’ NBC News. https://www.nbcnews.com/think/opinion/i-m-fighting-coronavirus-frontlines-yet-i-ve-heard-pandemic-ncna1175426
   Google Scholar
• Reich, J., Tingley, D. H., Leder-Luis, J., Roberts, M., & Stewart, B. (2015). Computer-assisted reading and discovery for student-generated text in massive open online courses. Journal of Learning Analytics, 2(1), 156–184. https://doi.org/10.18608/jla.2015.21.8
   Google Scholar
• Reuters. (2020). Fact check: Joe Biden did not call ‘call it a day’ at 9 a.m on Oct. 25. https://www.reuters.com/article/uk-factcheck-biden-lid-9/fact-check-joe-biden-did-not-call-call-it-a-day-at-9-a-m-on-oct-25-idUSKBN27C25F
   Google Scholar
• Rhee, J. W. (1997). Strategy and issue frames in election campaign coverage: A social cognitive account of framing effects. The Journal of Communication, 47(3), 26–48. https://doi.org/10.1111/j.1460-2466.1997.tb02715.x
   Web of Science ®Google Scholar
• Roberts, M. E., Stewart, B. M., Tingley, D., & Airoldi, E. M. (2013, December). The structural topic model and applied social science. In Advances in neural information processing systems workshop on topic models: Computation, application, and evaluation (Vol. 4, pp. 1–20).
   Google Scholar
• Romer, D., & Jamieson, K. H. (2020). Conspiracy theories as barriers to controlling the spread of COVID-19 in the US. Social Science & Medicine, 263, 113356. https://doi.org/10.1016/j.socscimed.2020.113356
   PubMed Web of Science ®Google Scholar
• Rothgerber, H., Wilson, T., Whaley, D., Rosenfeld, D. L., Humphrey, M., Moore, A. L., & Bihl, A. (2020). Politicizing the COVID-19 pandemic: Ideological differences in adherence to social distancing. PsyArXiv. https://doi.org/10.31234/osf.io/k23cv
   Google Scholar
• Rupar, A. (2020, March 20). Hannity claims he’s “never called the virus a hoax” 9 days after decrying Democrats’ “new hoax.” Vox. https://www.vox.com/2020/3/20/21186727/hannity-coronavirus-coverage-fox-news
   Google Scholar
• Shah, D. V., Domke, D., & Wackman, D. B. (1996). “To thine own self be true”: Values, framing, and voter decision-making strategies. Communication Research, 23(5), 509–560. https://doi.org/10.1177/009365096023005001
   Web of Science ®Google Scholar
• Southwell, B. G., & Thorson, E. A. (2015). The prevalence, consequence, and remedy of misinformation in mass media systems. The Journal of Communication, 65(4), 589–595. https://doi.org/10.1111/jcom.12168
   Web of Science ®Google Scholar
• Spiering, C. (2020, March 23). Nancy Pelosi proposes 1,400-page Coronavirus bill stuffed with pork. Breitbart. https://www.breitbart.com/politics/2020/03/23/nancy-pelosi-proposes-1120-page-coronavirus-bill-stuffed-with-pork/
   Google Scholar
• Stecuła, D. (2020, April 6). What do we know about misinformation during the coronavirus outbreak?. Mischiefs of Faction. https://www.mischiefsoffaction.com/post/what-do-we-know-about-misinformation-during-the-coronavirus-outbreak
   Google Scholar
• Stroebe, W., vanDellen, M. R., Abakoumkin, G., Lemay, E. P., Jr., Schiavone, W. M., Agostini, M., Bélanger, J. J., Gützkow, B., Kreienkamp, J., Margit Reitsema, A., Abdul Khaiyom, J. H., Ahmedi, V., Akkas, H., Almenara, C. A., Atta, M., Bagci, S. C., Basel, S., Kida, E. B., Bernardo, A. B. I., Leander, N. P. (2021). Politicization of COVID-19 health-protective behaviors in the United States: Longitudinal and cross-national evidence. Plos One, 16(10), e0256740. https://doi.org/10.1371/journal.pone.0256740
   PubMed Web of Science ®Google Scholar
• Stroud, N. J. (2007). Media effects, selective exposure, and Fahrenheit 9/11. Political Communication, 24(4), 415–432. https://doi.org/10.1080/10584600701641565
   Web of Science ®Google Scholar
• Stroud, N. J. (2011). Niche news: The politics of news choice. Oxford University Press.
   Google Scholar
• Stroud, N. J. (2018). Selective exposure theories. In K. Kenski & K. Jamieson (Eds.), The Oxford handbook of political communication (pp. 531–548). Oxford University Press. https://doi.org/10.1093/oxfordhb/9780199793471.013.009_update_001
   Google Scholar
• Van Boekel, M., Lassonde, K. A., O’Brien, E. J., & Kendeou, P. (2017). Source credibility and the processing of refutation texts. Memory & Cognition, 45(1), 168–181. https://doi.org/10.3758/s13421-016-0649-0
   PubMed Web of Science ®Google Scholar
• van Gorp, B. (2010). Strategies to take subjectivity out of framing analysis. In P. D’Angelo (Ed.), Doing news framing analysis: Empirical and theoretical perspectives (pp. 100–125). Routledge.
   Google Scholar
• Van Scoy, L. J., Snyder, B., Miller, E. L., Toyobo, O., Grewel, A., Ha, G., Gillespie, S., Pate, M., Reilly, J., Zgierska, A. E., & Lennon, R. P. (2021). Public anxiety and distrust due to perceived politicization and media sensationalism during early COVID-19 media messaging. Journal of Communication in Healthcare, 14(3), 193–205. https://doi.org/10.1080/17538068.2021.1953934
   Google Scholar
• WHO. (2021). Infodemic. https://www.who.int/health-topics/infode.
   Google Scholar
• Zhao, E., Wu, Q., Crimmins, E. M., & Ailshire, J. A. (2020). Media trust and infection mitigating behaviours during the COVID-19 pandemic in the USA. BMJ Global Health, 5(10), e003323. https://doi.org/10.1136/bmjgh-2020-003323
   PubMed Web of Science ®Google Scholar