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Volume 7, Issue 1
  • E-ISSN: 2665-9085
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Abstract

Abstract

During the COVID-19 pandemic, wearing a face mask became politicized in the United States, with politicians and reporters employing competing public safety and civil liberties frames in discussions of masking. In this research, we argue that political candidates’ decisions to speak about and depict mask-wearing in their political advertising were strategic, depending on both the candidate’s party and gender. We examine political ads run on Facebook and on television by federal candidates during the 2020 U.S. campaigns. We use Amazon’s deep learning algorithms for PPE (personal protective equipment) detection. We extract the text and audio of each ad to identify mentions of masks and use an à la Carte embedding regression model to understand how the usage of the term mask differs across covariates. We find that images of masks are much more common than mentions of masks, that there are significant partisan, but not gender, differences in the use of masks, and that there are both partisan and gender differences in the way that candidates speak about masking. This research demonstrates the utility of a novel approach to collecting data. It also suggests that public health measures can become partisan in a campaign environment, with the potential to polarize both the views and behaviors of Democrats and Republicans.

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2025-11-01
2025-12-05
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References

  1. Barry, C. L., Bandara, S., Fowler, E. F., Baum, L., Gollust, S. E., Niederdeppe, J., & Kennedy-Hendricks, A. (2020). Guns in political advertising over four us election cycles, 2012 to 2018. Health affairs (Project Hope), 39(2), 327–333. https://doi.org/10.1377/hlthaff.2019.01102
     [Google Scholar]
  2. Brader, T. (2005). Striking a responsive chord: How political ads motivate and persuade voters by appealing to emotions. American Journal of Political Science, 49(2), 388–405.
     [Google Scholar]
  3. Carpinella, C., & Bauer, N. M. (2021). A visual analysis of gender stereotypes in campaign advertising. Politics, Groups, and Identities, 9(2), 369–386.
     [Google Scholar]
  4. Connaughton, S. L., & Jarvis, S. E. (2004). Invitations for partisan identification: Attempts to court Latino voters through televised Latino-oriented political advertisements, 1984–2000. Journal of Communication, 54(1), 38–54. https://doi.org/10.1111/j.1460-2466.2004.tb02612.x
     [Google Scholar]
  5. Daily Kos Election. (2016). Daily Kos elections’ guide. https://docs.google.com/spreadsheets/d/1XbUXnI9OyfAuhP5P3vWtMuGc5UJlrhXbzZo3AwMuHtk/edit%5C#gid=0
  6. Dan, V., & Arendt, F. (2021). Visual cues to the hidden agenda: Investigating the effects of ideology-related visual subtle backdrop cues in political communication [Publisher: SAGE Publications Inc]. The International Journal of Press/Politics, 26(1), 22–45. https://doi.org/10.1177/1940161220936593
     [Google Scholar]
  7. Darmofal, D. (2005). Elite cues and citizen disagreement with expert opinion. Political Research Quarterly, 58(3), 381–395.
     [Google Scholar]
  8. Dittmar, K. (2015). Navigating gendered terrain: Stereotypes and strategy in political campaigns. Temple University Press.
     [Google Scholar]
  9. Dolan, K., & Lynch, T. (2017). Do candidates run as women and men or Democrats and Republicans? The impact of party and sex on issue campaigns. Journal of Women, Politics & Policy, 38(4), 522–546.
     [Google Scholar]
  10. Fowler, E. F., Franz, M. M., Martin, G. J., Peskowitz, Z., & Ridout, T. N. (2021). Political advertising online and offline. American Political Science Review, 115(1), 130–149.
     [Google Scholar]
  11. Fowler, E. F., Franz, M. M., & Ridout, T. N. (2021). Political advertising in the United States (2nd). Routledge.
     [Google Scholar]
  12. 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.
     [Google Scholar]
  13. Fowler, E. F., & Ridout, T. N. (2009). Local television and newspaper coverage of political advertising. Political Communication, 26(2), 119–136. https://doi.org/10.1080/10584600902850635
     [Google Scholar]
  14. Gadarian, S. K., Goodman, S. W., & Pepinsky, T. B. (2021). Partisanship, health behavior, and policy attitudes in the early stages of the COVID-19 pandemic [Publisher: Public Library of Science]. PLOS ONE, 16(4), e0249596. https://doi.org/10.1371/journal.pone.0249596
     [Google Scholar]
  15. Gillespie, A. (2018). Race and the Obama administration: Substance, symbols, and hope. Manchester University Press.
     [Google Scholar]
  16. Gollust, S. E., Nagler, R. H., & Fowler, E. F. (2020). The emergence of COVID-19 in the US: A public health and political communication crisis. Journal of Health Politics, Policy and Law, 45(6), 967–981. https://doi.org/10.1215/03616878-8641506
     [Google Scholar]
  17. Gramlich, J. (2022). Two years into the pandemic, Americans inch closer to a new normal. Pew Research Center. https://www.pewresearch.org/2022/03/03/two-years-into-the-pandemic-americans-inch-closer-to-a-new-normal/
     [Google Scholar]
  18. 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.
     [Google Scholar]
  19. Hajnal, Z. L. (2006). Changing white attitudes toward black political leadership (1st edition). Cambridge University Press.
     [Google Scholar]
  20. Hayes, D. (2011). When gender and party collide: Stereotyping in candidate trait attribution. Politics & Gender, 7(2), 133–165.
     [Google Scholar]
  21. Holman, M. R., Boussalis, C., & Coan, T. (2022). Masking concern: Congressional social media images and concern about COVID-19. APSA Annual Meeting & Exhibition. Retrieved March25, 2022, from https://tinyurl.com/y6fxgfmz
     [Google Scholar]
  22. Huang, J., Fisher, B. T., Tam, V., Wang, Z., Song, L., Shi, J., La Rochelle, C., Wang, X., Morris, J. S., Coffin, S. E., & Rubin, D. M. (2022). The effectiveness of government masking mandates on COVID-19 county-level case incidence across the United States, 2020 [Publisher: Health Affairs]. Health Affairs, 41(3), 445–453. https://doi.org/10.1377/hlthaff.2021.01072
     [Google Scholar]
  23. Huddy, L., & Capelos, T. (2002). Gender stereotyping and candidate evaluation. In The social psychology of politics (pp. 29–53). Springer.
     [Google Scholar]
  24. Huddy, L., & Terkildsen, N. (1993). Gender stereotypes and the perception of male and female candidates. American Journal of Political Science, 119–147.
     [Google Scholar]
  25. Ike, J. D., Bayerle, H., Logan, R. A., & Parker, R. M. (2020). Face masks: Their history and the values they communicate. Journal of Health Communication, 25(12), 990–995. https://doi.org/10.1080/10810730.2020.1867257
     [Google Scholar]
  26. Khodak, M., Saunshi, N., Liang, Y., Ma, T., Stewart, B., & Arora, S. (2018). A la carte embedding: Cheap but effective induction of semantic feature vectors. Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 12–22. https://doi.org/10.18653/v1/P18-1002
     [Google Scholar]
  27. King, D. C., & Matland, R. E. (2003). Sex and the grand old party: An experimental investigation of the effect of candidate sex on support for a Republican candidate. American Politics Research, 31(6), 595–612.
     [Google Scholar]
  28. Kramer, S. (2020). More Americans say they are regularly wearing masks in stores and other businesses. Retrieved March23, 2022, from https://www.pewresearch.org/fact-tank/2020/08/27/more-americans-say-they-are-regularly-wearing-masks-in-stores-and-other-businesses/
     [Google Scholar]
  29. Laver, M., Benoit, K., & Garry, J. (2003). Extracting policy positions from political texts using words as data. American Political Science Review, 97(2), 311–331. https://doi.org/10.1017/S0003055403000698
     [Google Scholar]
  30. Layman, G. C., Carsey, T. M., & Horowitz, J. M. (2006). Party polarization in American politics: Characteristics, causes, and consequences. Annu. Rev. Polit. Sci., 9, 83–110.
     [Google Scholar]
  31. Liptak, K. (2020). Trump announces new face mask recommendations after heated internal debate. CNN. https://www.cnn.com/2020/04/03/politics/trump-white-house-face-masks/index.html
     [Google Scholar]
  32. Little, T. H., Dunn, D., & Deen, R. E. (2001). A view from the top: Gender differences in legislative priorities among state legislative leaders. Women & Politics, 22(4), 29–50.
     [Google Scholar]
  33. Mikolov, T., Sutskever, I., Chen, K., Corrado, G. S., & Dean, J. (2013). Distributed representations of words and phrases and their compositionality, 9.
     [Google Scholar]
  34. Monroe, B. L., Colaresi, M. P., & Quinn, K. M. (2008). Fightin’ words: Lexical feature selection and evaluation for identifying the content of political conflict. Political Analysis, 16(4 SPEC. ISS.), 372–403. https://doi.org/10.1093/pan/mpn018
     [Google Scholar]
  35. Montgomery, D. (2020). Citylab congressional density index. CityLab. Retrieved from: https://github.com/theatlantic/citylab-data/blob/master/citylab-congress/citylab_cdi.csv.
     [Google Scholar]
  36. Mordecai, M., & Connaughton, A. (2020). Public opinion about coronavirus is more politically divided in U.S. than in other advanced economies. Pew Research Center. Retrieved September20, 2021, from https://www.pewresearch.org/fact-tank/2020/10/28/public-opinion-about-coronavirus-is-more-politically-divided-in-u-s-than-in-other-advanced-economies/
     [Google Scholar]
  37. Neumann, M., Fowler, E. F., & Ridout, T. N. (2022). Body language and gender stereotypes in campaign video. Computational Communication Research, 4(1).
     [Google Scholar]
  38. Neumann, M., Moore, S. T., Baum, L. M., Oleinikov, P., Xu, Y., Niederdeppe, J., Lewis Jr, N., Gollust, S. E., & Fowler, E. F. (2024). Politicizing masks? examining the volume and content of local news coverage of face coverings in the us through the covid-19 pandemic. Political Communication, 41(1), 66–106.
     [Google Scholar]
  39. Osborn, T. L. (2012). How women represent women: Political parties, gender and representation in the state legislatures. Oxford University Press, USA.
     [Google Scholar]
  40. Palmer, C. L., & Peterson, R. D. (2020). Toxic mask-ulinity: The link between masculine toughness and affective reactions to mask wearing in the COVID-19 era [Publisher: Cambridge University Press]. Politics & Gender, 16(4), 1044–1051. https://doi.org/10.1017/S1743923X20000422
     [Google Scholar]
  41. Roberts, M. E., Stewart, B. M., Tingley, D., Lucas, C., Leder-Luis, J., Gadarian, S. K., Albertson, B., & Rand, D. G. (2014). Structural topic models for open-ended survey responses. American Journal of Political Science, 58(4), 1064–1082. https://doi.org/10.1111/ajps.12103
     [Google Scholar]
  42. Robertson, N. (2020). Trump doesn’t think us needs a national mask mandate. CNN. https://www.cnn.com/2020/07/18/politics/trump-us-mask-mandate-coronavirus/index.html
     [Google Scholar]
  43. Rodriguez, P. L., Spirling, A., & Stewart, B. M. (2021). Embedding regression: Models for context-specific description and inference (tech. rep.). Working Paper Vanderbilt University.
     [Google Scholar]
  44. Roll Call. (2020). Roll call election guide. https://www.rollcall.com/election-guide-house/
  45. Sapiro, V., Cramer Walsh, K., Strach, P., & Hennings, V. (2011). Gender, context, and television advertising: A comprehensive analysis of 2000 and 2002 House races. Political Research Quarterly, 64(1), 107–119.
     [Google Scholar]
  46. Schill, D. (2012). The visual image and the political image: A review of visual communication research in the field of political communication. Review of Communication, 12(2), 118–142.
     [Google Scholar]
  47. Schmuck, D., & Matthes, J. (2017). Effects of economic and symbolic threat appeals in right-wing populist advertising on anti-immigrant attitudes: The impact of textual and visual appeals. Political Communication, 34(4), 607–626. https://doi.org/10.1080/10584609.2017.1316807
     [Google Scholar]
  48. Schneider, E. (2020). The face mask ‘is almost as much of a symbol as a MAGA hat’. Politico. https://www.politico.com/news/2020/09/30/face-masks-political-ads-coronavirus-424149
     [Google Scholar]
  49. Schneider, M. C., & Bos, A. L. (2016). The interplay of candidate party and gender in evaluations of political candidates. Journal of Women, Politics & Policy, 37(3), 274–294.
     [Google Scholar]
  50. Scoville, C., McCumber, A., Amironesei, R., & Jeon, J. (2022). Mask refusal backlash: The politicization of face masks in the American public sphere during the early stages of the covid-19 pandemic. Socius, 8.
     [Google Scholar]
  51. Shapiro, R. Y., & Mahajan, H. (1986). Gender differences in policy preferences: A summary of trends from the 1960s to the 1980s. Public Opinion Quarterly, 50(1), 42–61.
     [Google Scholar]
  52. Sides, J. (2006). The origins of campaign agendas. British Journal of Political Science, 36(3), 407–436.
     [Google Scholar]
  53. Stephens-Dougan, L. (2020). Race to the bottom: How racial appeals work in American politics. University of Chicago Press. Retrieved March29, 2022, from https://press.uchicago.edu/ucp/books/book/chicago/R/bo50271574.html
     [Google Scholar]
  54. Stolberg, S. G. (2020). Biden’s call for ‘national mask mandate’ gains traction in public health circles. New York Times. https://www.nytimes.com/2020/10/29/us/politics/trump-biden-mask-mandate.html
     [Google Scholar]
  55. Strach, P., & Sapiro, V. (2011). Campaigning for congress in the “9/11” era: Considerations of gender and party in response to an exogenous shock. American Politics Research, 39(2), 264–290.
     [Google Scholar]
  56. Swigger, N. (2012). What you see is what you get: Drawing inferences from campaign imagery. Political Communication, 29(4), 367–386.
     [Google Scholar]
  57. Tesler, M. (2020). Raphael Warnock’s dog ads cut against white voters’ stereotypes of black people. Retrieved March23, 2022, from https://fivethirtyeight.com/features/raphael-warnocks-dog-ads-cut-against-white-voters-stereotypes-of-black-people/
     [Google Scholar]
  58. U.S. Census Bureau. (2020). American community survey 5-year data (2009-2019).
  59. Valentino, N. A., Hutchings, V. L., & White, I. K. (2002). Cues that matter: How political ads prime racial attitudes during campaigns [Publisher: Cambridge University Press]. American Political Science Review, 96(1), 75–90. https://doi.org/10.1017/S0003055402004240
     [Google Scholar]
  60. Valentino, N. A., Hutchings, V. L., & Williams, D. (2004). The impact of political advertising on knowledge, internet information seeking, and candidate preference. Journal of Communication, 54(2), 337–354.
     [Google Scholar]
  61. Wallace, J., Goldsmith-Pinkham, P., & Schwartz, J. L. (2022). Excess death rates for Republicans and Democrats during the COVID-19 pandemic (tech. rep.). National Bureau of Economic Research.
     [Google Scholar]
  62. Young, D. G., Rasheed, H., Bleakley, A., & Langbaum, J. B. (2022). The politics of mask-wearing: Political preferences, reactance, and conflict aversion during COVID. Social Science & Medicine (1982), 298, 114836. https://doi.org/10.1016/j.socscimed.2022.114836
     [Google Scholar]
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Candidate Party, Gender, and the Face Mask as a Political Symbol in Campaign Advertisements
CCR 7, 1 (2025); https://doi.org/10.5117/CCR2025.1.002.YAO
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Keyword(s): COVID-19; masks; political advertising

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