“The New Gay Plague”: Mixed-Method Analysis of Public Attitudes Toward Mpox
Tej Shah, Walter Payton College Preparatory, Chicago, Illinois, United States
Mpox—previously monkeypox—was declared a public health emergency on August 4, 2022, in the United States. The emerging isolation of the virus in the LGBTQ+ community—particularly among gay, bisexual, and men who have sex with men (GBMSM)—led many to draw parallels between the emerging multi-country outbreak and the 1980s HIV/AIDS crisis. The purpose of this study was to investigate media framing of the mpox outbreak in American media through the lens of HIV social constructionist theory. Content analysis of a sample of 59 articles from the top-five most viewed U.S. media outlets provided a foundation to analyze quantitative word frequency trends in mpox-related tweets (n=255,363). Results found that coverage often framed mpox as a product of GBMSM hypersexuality, leading to potentially stigmatizing attitudes and a drastic increase in mpox tweet content related to sexual activity. While greater attention to stigma was observed in coverage, blame attribution to populations, governments, and practices was one of the most common frames across all media sources. Heavy reporting of systemic barriers to vaccination, testing, or diagnosis serve as continuities from HIV/AIDS and COVID-19 epidemics, underscoring fears around a second plague and influencing public attitudes. Mpox conspiracy theories also proliferated heavily on Twitter, with a noticeable increase in conspiracy language over time. These findings can inform the social realities of mpox, an understudied dimension, of which an understanding is vital to implementing services that address all elements of the ongoing outbreak.
On May 7, 2022, the National IHR Focal Point for the United Kingdom notified the World Health Organization (WHO) of a confirmed case of human mpox (MPX) in an individual who had traveled from the United Kingdom to Nigeria (CDC, 2022a). While the virus has been endemic in Central and West African regions since 1970 (Kozlov, 2022), it has rarely occurred outside of the African Continent. After the U.K case was identified, however, MPX quickly spread through non-endemic areas, including Europe and North America (Thornhill et al., 2022). As of October 2022, there have been over 69,244 confirmed cases across over 107 countries, the majority of which are historically non-endemic (CDC, 2022a). Additionally, the novel, disproportionate spread of the virus among gay, bisexual, and other men who have sex with men (GBMSM)—over 98% of total cases in the United States (Thornhill et al., 2022)—has engendered potentially stigmatizing, misinformative rhetoric from news media sites and the general public alike (Chang et al., 2022). This distinct prevalence in the LGBTQ+ community has caused many to draw parallels between the current MPX crisis and 1980s HIV/AIDS epidemic (Diamond, 2022). While these two viruses are hardly alike, the influential role of media in shaping perceptions and attitudes towards both MPX and HIV is evident.
Sociologists, public health officials, and HIV scholars often engage the idea of media frames in the contexts of social constructionism (Herek et al., 2003; McCauley et al., 2013; Tierney et al., 2006). The way an idea is framed, much like language at large, can simultaneously highlight its specific elements while hiding others (Gamson et al., 1992). As such, media forms i.e. news content, do not simply reflect reality: they define it (Secrist, 1986). The discursive use of metaphors, narrative maneuvers, or personal bias play significant roles in shaping collective knowledge, leaning into the interpretation of the world around us (Yan, 2020). As the world is revolutionized by globalization and technological progress, more and more as individuals we “walk around with media-generated images of the world, using them to construct meaning about political and social issues” (Gamson et al., 1992).
The increasing prevalence of social media is changing the ways in which information on world issues is gathered, disseminated, and discussed. In the United States, more than half of U.S. adults report getting news via social media “often” or “sometimes” (Liedke & Matsa, 2022). Twitter is one of the most popular social media and microblogging sites. In 2022, over 500 million tweets were posted per day (Sayce, 2022). Literature demonstrates that tweet content specifically can be used to analyze public health topics, namely public opinion on COVID-19 (Boon-Itt & Skunkan, 2020) and HPV vaccination (Surian et al., 2016).
This paper employs a sequential explanatory mixed-method design to analyze qualitative content analyses of news articles pertaining to attitudes around human mpox (MPX) in the United States and quantitative data from relevant tweets (n=255,363). Ethical approval was not necessary as the sample of tweets used in the analysis are publicly available information posted on social media, available via the Harvard Dataverse project.
News articles were selected using the top five most visited sites in July 2022: New York Times, CNN, Fox News, MSN, and New York Post (Similarweb, 2022). Headlines and paragraphs were searched using four different combinations: monkeypox and the United States and MSM, monkeypox and the United States and men who have sex with men, monkeypox and the United States and gay, and monkeypox and the United States and LGBTQ. Secondary filtering was done to exclude results that were solely video content, did not focus on the United States, or briefly mentioned mpox. After the second round of selection, 59 articles remained. Dedoose was used to perform the inductive content analysis, generate a coding scheme, and record overlying themes.
For quantitative analysis, an open-source approach is presented in which tweets were collected from the Harvard Dataverse (Thakur, 2022), and then analyzed and visualized using R programming. Informed by the qualitative findings, a list of 100 codewords was generated using the keyword network technique (Ávila-Toscano et al., 2018). Keywords were searched and filtered within tweets to analyze trends over time.
A total of 59 articles were identified between July 1, 2022 and August 8, 2022 after screening and sorting from the 5 online newspapers (CNN: 18, New York Times: 18, MSN: 9, Fox News: 7, New York Post: 6). In terms of political bias, three sources (CNN, NYT, and MSN) were identified as political centrist and left-leaning, while two sources (NYP and FOX) were identified as right-leaning (Allsides, 2019). New York Times had the most monthly viewers at 458.7 million in July 2022, while the New York Post had the least at 163.9 million; all other selected sites fell within this range.
The top three most prominent topics were vaccination (n = 49, 85.9%), MSM (n = 46, 77.96%), and inequities (n = 36, 61.01%). (See Table 1 for examples of content findings.) The blame frame was the fourth most common frame (n = 34, 57.62%) in American news, summarized in Table 2. Additionally, failure framing found itself in almost half of all articles. (n = 28, 47.46%). Table 3. and Table 4. provide examples of reported barriers to successful vaccination, testing, or implementation or success of any other public health intervention.
A total of 255,363 tweets were quantitatively analyzed from 4 data ranges: May 7, 2022–May 21, 2022 (May), June 5, 2022–June 11, 2022 (Early June), June 12, 2022–June 30, 2022 (Mid to Late June), and July 1, 2022–July 23, 2022 (July). This timeframe represents the months between the first 2022 case of mpox and the WHO declaration as a global health emergency. Search terms fell into six categories: LGBTQ+ (n=15, 14.85%), sexual activity (n=22, 21.78%), public health (n=7, 6.93%), conspiracy (n=33, 32.67%), COVID-19 (n=7, 6.93%), politics (n=11, 10.89%), and religion (n=5, 4.95%).
Figure 1: Frequencies of select keywords related to sex and sexuality theme in May, early June, Mid to Late June, and July of 2022. Keywords were determined by reference to sexual acts or
objects, as well as environments in which they might occur.
Figure 2: Frequencies of select keywords related to LGBTQ+ theme from May, early June, Mid to
Late June, and July of 2022. Keywords were determined by reference to the LGBTQ+ community as well as phenomena, events, and circumstances they may be associated with.
Figure 3: Frequencies of select keywords related to politics theme from May, early June, Mid to
Late June, and July of 2022. Keywords were determined by reference to the American political system and key stakeholders in it.
Figure 4: Frequencies of select keywords related to conspiracy theme from May, early June, Mid to Late June, and July of 2022. Keywords were determined by reference to common conspiracies
as well as references to debunked or false claims about the U.S. public health or political system.
Figure 5: Frequencies of select keywords related to public health theme from May, early June, Mid to Late June, and July of 2022.
Figure 6: Frequencies of select keywords related to religion theme from May to July of 2022
Figure 7: Frequencies of select keywords related to COVID-19 theme from May to July of 2022.
Content analysis of mpox media coverage reveals several clear trends that emerge over the 1-month period spanned by the selected sources. First, inclusivity in public health has increased drastically since the 1980s HIV/AIDS epidemic. Journalists and media providers are paying more attention to stigma and wording choices. Our qualitative findings indicate that greater attention to stigmatization was expressed in almost half of the articles (n=28, 47.46%). Articles were observed referencing LGBTQ+ representatives or organizations, or even detailing the history of the HIV/AIDS epidemic e.g. “...ACT UP, which formed in 1987 in response to government inaction on H.I.V./AIDS.” This optimistic finding, in the context of past media behavior during HIV/AIDS (Brodie et al., 2004; Persson & Newman, 2008), illustrates growth since the media-corroborated stigma of the COVID-19 pandemic (Yang et al., 2021).
Despite the progress that has been made, the media response has been far from perfect. The use of contradictory and misinformative comparisons in public media coupled with a lack of accountability, created divergent realities of mpox in the United States, many of which are thematically present in tweet data. Writers were seen framing mpox simultaneously as something that will ‘spill over’ into the general population and a ‘non-issue,’ as well as comparing the virus to an STI like HIV that it is not an STI. These frames are correlated with an increase in the presence of keywords ‘STI’ and in tweets from the analysis period (Fig 1). These findings are in line with existing research suggesting that competing narratives contribute to polarizing ideas and general confusion (Eliaz & Spiegler, 2020; Kennedy-Hendricks et al., 2016).
Additionally, reported failure of the ring vaccination strategy implemented by federal and regional policymakers was often pinned on GBMSM. With success contingent on the vaccination of contacts of confirmed mpox patients, public health officials quickly found that anonymous sexual encounters among GBMSM were constraining contact tracing. However, an abundance of existing literature demonstrates that this cultural practice is documented (Garcia et al., 2012). Instead of considering the inappropriateness of ring vaccination for this population, articles tended to associate this failure with clubs of “half dressed men” or “a hot and heavy festival season.” The use of the hypersexual frame could be attributed to the construction of mpox meanings that stigmatize behaviors of GBMSM. Descriptive statistics of tweets showed that keywords related to the sexual activity theme increased substantially from May to July. For example, the presence of terms ‘orgies’ increased by between 1700% and 5900% in the 2 months analyzed. The presence of words like ‘pride’ or ‘party’ also showed increases over time, likely continuing the sexualization of GBMSM culture (Lott et al., 2022).
Quantitative analysis of tweet content unexpectedly exposed the ongoing proliferation of conspiracy-based misinformation on social media. The presence of keywords ‘gates,’ ‘propaganda,’ ‘plan’ or ‘plandemic,’ ‘hoax,’ ‘fauci,’ and others all increased substantially in the 2 months of data collection. Additionally, conspiracy themes were observed to overlap with others. For example, the presence of terms ‘ballot’ or ‘vote’ within the politics theme often coincided with the above conspiracy keywords; interestingly, users suggested that the emerging mpox outbreak was an engineered effort to return to mail-in voting and falsify election outcomes. In this same way, ‘wuhan’ from the COVID-19 theme often joined conspiracy keywords with users insinuating that the same lab that created and released the novel coronavirus released the circulating mpox virus. These findings affirm previous research on Twitter misinformation (Jin et al., 2014; Oyeyemi et al., 2014; Sharma et al., 2020), providing new insight into sociodigital patterns relating to infectious disease and the growing need to curb misinformation on digital platforms.
Evidence shows there is a relationship between media framing and the construction of social paradigms (Adoni & Mane, 1984). The findings of this study offer insights and opportunities to address public attitudes to not only media providers but policymakers and public health decision-makers. First, media sources should be aware of the implications of word choice and interpretive issue framing. This capacity may create barriers to public health interventions like vaccination, testing, or even general awareness. As such, journalists must ensure that mpox frames are accurate and understanding and do not give rise to personal biases. To the author’s knowledge, this is the first study delving into the social realities of mpox in the United States. Greater work by anthropologists, sociologists, and other social scientists delving into meanings of mpox illness rather than the solely biological virus is necessary to the development of a clear picture of this ongoing outbreak.
Adoni, H., & Mane, S. (1984). MEDIA AND THE SOCIAL CONSTRUCTION OF REALITY: Toward an Integration of Theory and Research. Communication Research, 11(3), 323–340. https://doi.org/10.1177/009365084011003001
Allsides. (2019, February 21). Media Bias Chart. AllSides. https://www.allsides.com/media-bias/media-bias-chart
Anwar, A., Malik, M., Raees, V., & Anwar, A. (2020). Role of Mass Media and Public Health Communications in the COVID-19 Pandemic. Cureus, 12(9), e10453. https://doi.org/10.7759/cureus.10453
Ávila-Toscano, J. H. , Romero-Pérez, I. C. , AiledMarenco-Escuderos, A., & Guajardo, E. S. (2018). Identification of Research Thematic Approaches Based on Keywords Network Analysis in Colombian Social Sciences. In (Ed.), Data Mining. IntechOpen. https://doi.org/10.5772/intechopen.76834
Backstrom, C. H., & Robins, L. S. (1998). The Media and AIDS. Journal of Health & Social Policy, 9(3), 45–69. https://doi.org/10.1300/J045v09n03_04
Berger, M. T. (2022). Coining Intersectional Stigma: Historical Erasures and The Future. American Journal of Public Health, 112(S4), S338–S339. https://doi.org/10.2105/AJPH.2022.306730
Boon-Itt, S., & Skunkan, Y. (2020). Public Perception of the COVID-19 Pandemic on Twitter: Sentiment Analysis and Topic Modeling Study. JMIR Public Health and Surveillance, 6(4), e21978. https://doi.org/10.2196/21978
Brier, J. (2018). Aids and Action (1980–1990s). In The Routledge History of Queer America. Routledge.
Brodie, M., Hamel, E., Brady, L. A., & Altman, D. E. (2004). AIDS at 21: Media Coverage of the HIV Epidemic 1981-2002. Columbia Journalism Review, 8.
CDC. (2022a, August 22). Monkeypox in the U.S. Centers for Disease Control and Prevention. https://www.cdc.gov/poxvirus/monkeypox/health-departments/vaccine-considerations.html
CDC. (2022b, September 22). Monkeypox Cases by Age and Gender, Race/Ethnicity, and Symptoms. https://www.cdc.gov/poxvirus/monkeypox/response/2022/demographics.html
Center for Biologics Evaluation and Research. (2021). JYNNEOS. FDA. https://www.fda.gov/vaccines-blood-biologics/jynneos
Chang, C. T., Thum, C. C., Lim, X. J., Chew, C. C., & Rajan, P. (2022). Monkeypox outbreak: Preventing another episode of stigmatisation. Tropical Medicine & International Health: TM & IH, 27(9), 754–757. https://doi.org/10.1111/tmi.13798
Cinelli, M., De Francisci Morales, G., Galeazzi, A., Quattrociocchi, W., & Starnini, M. (2021). The echo chamber effect on social media. Proceedings of the National Academy of Sciences, 118(9), e2023301118. https://doi.org/10.1073/pnas.2023301118
Cohen, C. J. (2009). The Boundaries of Blackness: AIDS and the Breakdown of Black Politics. University of Chicago Press. https://books.google.com/books?id=\_ZNfEAAAQBAJ
Conrad, P., & Barker, K. K. (2010). The Social Construction of Illness: Key Insights and Policy Implications. Journal of Health and Social Behavior, 51, S67–S79.
Corrigan, P. W., & Watson, A. C. (2002). Understanding the impact of stigma on people with mental illness. World psychiatry : official journal of the World Psychiatric Association (WPA), 1(1), 16–20.
Diamond, N. (2022, August 1). Remembering HIV and COVID-19 in Response to Monkeypox. Boston University School of Public Health. https://www.bu.edu/sph/news/articles/2022/remembering-hiv-and-covid-19-in-response-to-monkeypox/
Eliaz, K., & Spiegler, R. (2020). A Model of Competing Narratives. American Economic Review, 110(12), 3786–3816. https://doi.org/10.1257/aer.20191099
Foucault, M. (1961). Madness and Civilization: A History of Insanity in the Age of Reason. Psychology Press.
Frost, D. M. (2011). Social Stigma and its Consequences for the Socially Stigmatized. Social and Personality Psychology Compass, 5(11), 824–839. https://doi.org/10.1111/j.1751-9004.2011.00394.x
Gamson, W. A., Croteau, D., Hoynes, W., & Sasson, T. (1992). Media Images and the Social Construction of Reality. Annual Review of Sociology, 18, 373–393. http://www.jstor.org/stable/2083459
Garcia, J. R., Reiber, C., Massey, S. G., & Merriwether, A. M. (2012). Sexual Hookup Culture: A Review. Review of General Psychology : Journal of Division 1, of the American Psychological Association, 16(2), 161–176. https://doi.org/10.1037/a0027911
Gui, L. (2021). Media framing of fighting COVID-19 in China. Sociology of Health & Illness, 43(4), 966–970. https://doi.org/10.1111/1467-9566.13271
Hall, S. (Ed.). (1997). Representation: Cultural representations and signifying practices. (p. 400). Open University Press.
Heller, J. (2015). Rumors and Realities: Making Sense of HIV/AIDS Conspiracy Narratives and Contemporary Legends. American Journal of Public Health, 105(1), e43–e50. https://doi.org/10.2105/AJPH.2014.302284
Herek, G. M., Capitanio, J. P., & Widaman, K. F. (2003). Stigma, social risk, and health policy: Public attitudes toward HIV surveillance policies and the social construction of illness. Health Psychology, 22(5), 533–540. https://doi.org/10.1037/0278-618.104.22.1683
Iott, B. E., Loveluck, J., Benton, A., Golson, L., Kahle, E., Lam, J., Bauermeister, J. A., & Veinot, T. C. (2022). The impact of stigma on HIV testing decisions for gay, bisexual, queer and other men who have sex with men: A qualitative study. BMC Public Health, 22(1), 471. https://doi.org/10.1186/s12889-022-12761-5
Isidro, J., Borges, V., Pinto, M., Sobral, D., Santos, J. D., Nunes, A., Mixão, V., Ferreira, R., Santos, D., Duarte, S., Vieira, L., Borrego, M. J., Núncio, S., de Carvalho, I. L., Pelerito, A., Cordeiro, R., & Gomes, J. P. (2022). Phylogenomic characterization and signs of microevolution in the 2022 multi-country outbreak of monkeypox virus. Nature Medicine, 28(8), Article 8. https://doi.org/10.1038/s41591-022-01907-y
Islam, M. R., Hossain, M. J., Roy, A., Hasan, A., Rahman, M. A., Shahriar, M., & Bhuiyan, M. A. (2022). Repositioning potentials of smallpox vaccines and antiviral agents in monkeypox outbreak: A rapid review on comparative benefits and risks. Health science reports, 5(5), e798. https://doi.org/10.1002/hsr2.798
Jeffries, W. L., Townsend, E. S., Gelaude, D. J., Torrone, E. A., Gasiorowicz, M., & Bertolli, J. (2015). HIV Stigma Experienced by Young Men Who Have Sex With Men (MSM) Living With HIV Infection. AIDS Education and Prevention, 27(1), 58–71. https://doi.org/10.1521/aeap.2015.27.1.58
Jin, F., Wang, W., Zhao, L., Dougherty, E., Cao, Y., Lu, C., & Ramakrishnan, N. (2014). Misinformation Propagation in the Age of Twitter. Computer, 47(12), 90–94. https://doi.org/10.1109/MC.2014.361
Kennedy-Hendricks, A., McGinty, E. E., & Barry, C. L. (2016). Effects of Competing Narratives on Public Perceptions of Opioid Pain Reliever Addiction During Pregnancy. Journal of Health Politics, Policy and Law, 41(5), 873–916. https://doi.org/10.1215/03616878-3632230
Kindrachuk, J., Arsenault, R., Kusalik, A., Kindrachuk, K. N., Trost, B., Napper, S., Jahrling, P. B., & Blaney, J. E. (2012). Systems Kinomics Demonstrates Congo Basin Monkeypox Virus Infection Selectively Modulates Host Cell Signaling Responses as Compared to West African Monkeypox Virus. Molecular & Cellular Proteomics : MCP, 11(6), M111.015701. https://doi.org/10.1074/mcp.M111.015701
King, G., Schneer, B., & White, A. (2017). How the news media activate public expression and influence national agendas. Science, 358(6364), 776–780. https://doi.org/10.1126/science.aao1100
Kozlov, M. (2022). Monkeypox in Africa: The science the world ignored. Nature, 607(7917), 17–18. https://doi.org/10.1038/d41586-022-01686-z
Levenson, J. (2005). The Secret Epidemic: The Story of AIDS And Black America. Anchor Books. https://books.google.com/books?id=Ji6yHGpK3aUC
Liedke, J., & Eva Matsa, K. (2022). Social Media and News Fact Sheet. Pew Research Center’s Journalism Project. https://www.pewresearch.org/journalism/fact-sheet/social-media-and-news-fact-sheet/
Link, B. G., & Phelan, J. C. (2006). Stigma and its public health implications. The Lancet, 367(9509), 528–529. https://doi.org/10.1016/S0140-6736(06)68184-1
McCauley, M., Minsky, S., & Viswanath, K. (2013). The H1N1 pandemic: Media frames, stigmatization and coping. BMC Public Health, 13(1), 1116. https://doi.org/10.1186/1471-2458-13-1116
McCollum, A. M., & Damon, I. K. (2014). Human Monkeypox. Clinical Infectious Diseases, 58(2), 260–267. https://doi.org/10.1093/cid/cit703
McKay, R. A. (2017). Patient Zero and the Making of the AIDS Epidemic. University of Chicago Press. https://doi.org/10.7208/9780226064000
Messing, S., & Westwood, S. (2022). How Social Media Introduces Biases in Selecting and Processing News Content.
Murshed, B. A. H., Mallappa, S., Ghaleb, O. A. M., & Al-ariki, H. D. E. (2021). Efficient Twitter Data Cleansing Model for Data Analysis of the Pandemic Tweets. In I. Arpaci, M. Al-Emran, M. A. Al-Sharafi, & G. Marques (Eds.), Emerging Technologies During the Era of COVID-19 Pandemic (pp. 93–114). Springer International Publishing. https://doi.org/10.1007/978-3-030-67716-9_7
Myrick, R. (1998). AIDS Discourse: A Critical Reading of Mainstream Press Surveillance of Marginal Identity. Journal of Homosexuality, 35, 75–93. https://doi.org/10.1300/J082v35n01_04
New Mexico Department of Health. (2022). JYNNEOS VACCINE PROTOCOL for MONKEYPOX. https://www.nmhealth.org/publication/view/policy/7661/&cd=12&hl=en&ct=clnk&gl=us
NIH NIAID. (2022). ‘Monkeypox Virus’ [Photograph]. Flickr. https://www.flickr.com/photos/niaid/52096775365/in/photolist-2nnBAhV-2nnYSDr-2no175q-2nnYT5S-2nvmPCT-2nv1gAd-2nKgjoH-2nLH9wR-2nD9tHG-2nqG2Be-2nBWgDg-2nKgiXn-2nLFwWM-2nKfZcF-2nLH9tQ-2nAsrdu-2noeqP5-2nvmPKB-2nBVbmb-2nAzYUE-2noh3om-2nCt6oR-2nvpfEe-2nqJt4u-2nSAypX-2nHZPE8-2nGdwKm-2nnmEXh-2nAxHsT-2nAz9WK-2nAsFcG-2nAxFDc-2nBWksv-2nBVbCd-2nBJHCg-2nCkgvm-2nDbZJ8-2nD9yL9-2nKgWxh-2nLFw3Y-2nuQEaJ-2o12347-2nWnQaQ-2nWmSXe-2nJ25gx-2nnJV9s-2nBvz6u-2nZZZek-2no8C51-2nnHR6d
Oyeyemi, S. O., Gabarron, E., & Wynn, R. (2014). Ebola, Twitter, and misinformation: A dangerous combination? BMJ, 349. https://doi.org/10.1136/bmj.g6178
Persson, A., & Newman, C. (2008). Making monsters: Heterosexuality, crime and race in recent Western media coverage of HIV. Sociology of Health & Illness, 30(4), 632–646. https://doi.org/10.1111/j.1467-9566.2008.01082.x
Piot, P., Russell, S., & Larson, H. (2007). Good Politics, Bad Politics: The Experience of AIDS. American Journal of Public Health, 97(11), 1934–1936. https://doi.org/10.2105/AJPH.2007.121418
Platt, M. B., & Platt, M. O. (2013). From GRID to gridlock: The relationship between scientific biomedical breakthroughs and HIV/AIDS policy in the US Congress. Journal of the International AIDS Society, 16(1), 18446. https://doi.org/10.7448/IAS.16.1.18446
Reinka, M. A., Pan-Weisz, B., Lawner, E. K., & Quinn, D. M. (2020). Cumulative consequences of stigma: Possessing multiple concealable stigmatized identities is associated with worse quality of life. Journal of Applied Social Psychology, 50(4), 253–261. https://doi.org/10.1111/jasp.12656
Ribeiro, B., Hartley, S., Nerlich, B., & Jaspal, R. (2018, March). Media coverage of the Zika crisis in Brazil_ The construction of a ‘war’ frame that masked social and gender inequalities. https://doi.org/10.1016/j.socscimed.2018.01.023
Saki, M., Mohammad Khan Kermanshahi, S., Mohammadi, E., & Mohraz, M. (2015). Perception of Patients With HIV/AIDS From Stigma and Discrimination. Iranian Red Crescent Medical Journal, 17(6), e23638. https://doi.org/10.5812/ircmj.23638v2
Saksena, M. (2018). Framing Infectious Diseases: Effective Policy Implementation and United States Public Opinion. Doing Qualitative Research in Politics, 111–131. https://doi.org/10.1007/978-3-319-72230-6_6
Sastry, S., & Dutta, M. J. (2011). Postcolonial Constructions of HIV/AIDS: Meaning, Culture, and Structure. Health Communication, 26(5), 437–449. https://doi.org/10.1080/10410236.2011.554166
Sayce, D. (2022, August 3). The Number of tweets per day in 2022. David Sayce. https://www.dsayce.com/social-media/tweets-day/
Schubert, K. (2022). A New Era of Queer Politics? PrEP, Foucauldian Sexual Liberation, and the Overcoming of Homonormativity (SSRN Scholarly Paper No. 3901719). https://doi.org/10.2139/ssrn.3901719
Schutz, A. (1967). Phenomenology of the Social World. Northwestern University Press.
Secrist, M. M. (1986). Advertising, The Uneasy Persuasion. American Journalism, 3(2), 117–119. https://doi.org/10.1080/08821127.1986.10731067
Sharma, K., Seo, S., Meng, C., Rambhatla, S., Dua, A., & Liu, Y. (2020). Coronavirus on Social Media: Analyzing Misinformation in Twitter Conversations. arXiv. https://arxiv.org/abs/2003.12309v2
Sherlaw, W., & Raude, J. (2013). Why the French did not choose to panic: A dynamic analysis of the public response to the influenza pandemic. Sociology of Health & Illness, 35(2), 332–344. https://doi.org/10.1111/j.1467-9566.2012.01525.x
Sieff, E. (2003). Media frames of mental illnesses: The potential impact of negative frames. Journal of Mental Health, 12(3), 259–269. https://doi.org/10.1080/0963823031000118249
Similarweb. (2022, August 1). Top News And Media Websites Ranking in United States in July 2022. Similarweb. https://www.similarweb.com/top-websites/united-states/category/news-and-media/
Spitulnik, D. (1993). Anthropology and Mass Media. Annual Review of Anthropology, 22, 293–315.
Staniland, K., & Smith, G. (2013). Flu frames. Sociology of Health & Illness, 35(2), 309–324. https://doi.org/10.1111/j.1467-9566.2012.01537.x
Surian, D., Nguyen, D. Q., Kennedy, G., Johnson, M., Coiera, E., & Dunn, A. G. (2016). Characterizing Twitter Discussions About HPV Vaccines Using Topic Modeling and Community Detection. Journal of Medical Internet Research, 18(8), e6045. https://doi.org/10.2196/jmir.6045
Thakur, N. (2022). MonkeyPox2022Tweets: The First Public Twitter Dataset on the 2022 MonkeyPox Outbreak [Data set]. Harvard Dataverse. https://doi.org/10.7910/DVN/CR7T5E
Thornhill, J. P., Barkati, S., Walmsley, S., Rockstroh, J., Antinori, A., Harrison, L. B., Palich, R., Nori, A., Reeves, I., Habibi, M. S., Apea, V., Boesecke, C., Vandekerckhove, L., Yakubovsky, M., Sendagorta, E., Blanco, J. L., Florence, E., Moschese, D., Maltez, F. M., … Orkin, C. M. (2022). Monkeypox Virus Infection in Humans across 16 Countries—April–June 2022. New England Journal of Medicine, 387(8), 679–691. https://doi.org/10.1056/NEJMoa2207323
Tierney, K., Bevc, C., & Kuligowski, E. (2006). Metaphors Matter: Disaster Myths, Media Frames, and Their Consequences in Hurricane Katrina. The ANNALS of the American Academy of Political and Social Science, 604(1), 57–81. https://doi.org/10.1177/0002716205285589
Washer, P. (2004). Representations of SARS in the British newspapers. Social Science & Medicine (1982), 59(12), 2561–2571. https://doi.org/10.1016/j.socscimed.2004.03.038
WHO. (2022, July 23). WHO Director-General declares the ongoing monkeypox outbreak a Public Health Emergency of International Concern. World Health Organization (WHO). https://www.who.int/europe/news/item/23-07-2022-who-director-general-declares-the-ongoing-monkeypox-outbreak-a-public-health-event-of-international-concern
Wohn, D. Y., & Bowe, B. J. (2014). Crystallization: How social media facilitates social construction of reality. Proceedings of the Companion Publication of the 17th ACM Conference on Computer Supported Cooperative Work & Social Computing - CSCW Companion ’14, 261–264. https://doi.org/10.1145/2556420.2556509
World Health Organization. (2018). CURRENT STATUS OF MONKEYPOX DISEASE (Monkeypox, p. Page 7-Page 8). World Health Organization; JSTOR. http://www.jstor.org/stable/resrep39294.7
Wu, S., Hofman, J. M., Mason, W. A., & Watts, D. J. (2011). Who says what to whom on twitter. Proceedings of the 20th International Conference on World Wide Web - WWW ’11, 705. https://doi.org/10.1145/1963405.1963504
Yan, F. (2020). Image, Reality and Media Construction: A Frame Analysis of German Media Representations of China. Springer Singapore. https://doi.org/10.1007/978-981-32-9076-1
Yang, J. P., Nhan, E. R., & Tung, E. L. (2021). COVID-19 anti-Asian racism and race-based stress: A phenomenological qualitative media analysis. Psychological Trauma: Theory, Research, Practice, and Policy, No Pagination Specified-No Pagination Specified. https://doi.org/10.1037/tra0001131