130
Views
0
CrossRef citations to date
0
Altmetric
Research Article

Expressing Uncertainty and Risk About the Mpox Outbreak: A Textual Analysis of Twitter Messaging

, &

References

  • Afifi, W. A., Felix, E. D., & Afifi, T. D. (2012). The impact of uncertainty and communal coping on mental health following natural disasters. Anxiety, Stress, & Coping, 25(3), 329–347. https://doi.org/10.1080/10615806.2011.603048
  • Akhther, N., & Sopory. (2022). Seeking and sharing mental health information on social media during COVID-19: Role of depression and anxiety, peer support, and health benefits. The Journal of Technology in Behavioral Science, 7(2), 211–226. https://doi.org/10.1007/s41347-021-00239-x
  • Aljazeera. (2023). WHO declares monkeypox a global emergency amid surge in cases.https://www.aljazeera.com/news/2022/7/23/world-health-organisation-declares-monkeypox-a-global-emergency
  • Antinori, A., Mazzotta, V., Vita, S., Carletti, F., Tacconi, D., Lapini, L. E., D’Abramo, A., Cicalini, S., Lapa, D., Pittalis, S., Puro, V., Rivano Capparuccia, M., Giombini, E., Gruber, C. E. M., Garbuglia, A. R., Marani, A., Vairo, F., Girardi, E., Vaia, F., & Nicastri, E. (2022). Epidemiological, clinical and virological characteristics of four cases of mpox support transmission through sexual contact, Italy, May 2022. Eurosurveillance, 27(22), 2200421. https://doi.org/10.2807/1560-7917.ES.2022.27.22.2200421
  • Austin, L., Fisher Liu, B., & Jin, Y. (2012). How audiences seek out crisis information: Exploring the social-mediated crisis communication model. Journal of Applied Communication Research, 40(2), 188–207. https://doi.org/10.1080/00909882.2012.654498
  • Babrow, A. S., Kasch, C. R., & Ford, L. A. (1998). The many meanings of uncertainty in illness: Toward a systematic accounting. Health Communication, 10(1), 1–23. https://doi.org/10.1207/s15327027hc1001_1
  • Bäckström, C., Larsson, T., Wahlgren, E., Golsäter, M., Mårtensson, L. B., & Thorstensson, S. (2017). ‘It makes you feel like you are not alone’: Expectant first-time mothers’ experiences of social support within the social network, when preparing for childbirth and parenting. Sexual & Reproductive Healthcare, 12, 51–57. https://doi.org/10.1016/j.srhc.2017.02.007
  • Ball-Rokeach, S. J. (1985). The origins of individual media-system dependency: A sociological framework. Communication Research, 12(4), 485–510. https://doi.org/10.1177/009365085012004003
  • Barogna, S. (2022, July 30). Action on mpox accelerates in US as outbreak expands. Vox News. https://www.voanews.com/a/action-on-mpox-accelerates-in-us-as-outbreak-expands-/6680081.html
  • Basch, C. H., Basch, C. E., Hillyer, G. C., & Meleo-Erwin, Z. C. (2022). Social media, public health, and community mitigation of COVID-19: Challenges, risks, and benefits. Journal of Medical Internet Research, 24(4), e36804. https://doi.org/10.2196/36804
  • Bazarova, N. N., Choi, Y. H., Whitlock, J., Cosley, D., & Sosik, V. (2017). Psychological distress and emotional expression on Facebook. Cyberpsychology, Behavior, and Social Networking, 20(3), 157–163. https://doi.org/10.1089/cyber.2016.0335
  • BBC. (2023, May 5). Covid global health emergency is over, WHO says.https://www.bbc.com/news/health-65499929
  • Blei, D. M., Ng, A. Y., & Jordan, M. I. (2003). Latent dirichlet allocation. Journal of Machine Learning Research, 3(Jan), 993–1022.
  • Bode, L., & Vraga, E. K. (2018). See something, say something: Correction of global health misinformation on social media. Health Communication, 33(9), 1131–1140. https://doi.org/10.1080/10410236.2017.1331312
  • Brashers, D. E. (2001). Communication and uncertainty management. Journal of Communication, 51(3), 477–497. https://doi.org/10.1111/j.1460-2466.2001.tb02892.x
  • Brashers, D. E., Goldsmith, D. J., & Hsieh, E. (2002). Information seeking and avoiding in health contexts. Human Communication Research, 28(2), 258–271. https://doi.org/10.1111/j.1468-2958.2002.tb00807.x
  • Brashers, D. E., Neidig, J. L., Russell, J. A., Cardillo, L. W., Haas, S. M., Dobbs, L. K., Garland, M., McCartney, B., & Nemeth, S. (2003). The medical, personal, and social causes of uncertainty in HIV illness. Issues in Mental Health Nursing, 24(5), 497–522. https://doi.org/10.1080/01612840305292
  • Buchanan, R., & Beckett, R. D. (2014). Assessment of vaccination‐related information for consumers available on Facebook®. Health Information & Libraries Journal, 31(3), 227–234. https://doi.org/10.1111/hir.12073
  • Cascini, F., Pantovic, A., Al-Ajlouni, Y. A., Failla, G., Puleo, V., Melnyk, A., Lontano, A., & Ricciardi, W. (2022). Social media and attitudes towards a COVID-19 vaccination: A systematic review of the literature. EClinicalMedicine, 48, 101454. https://doi.org/10.1016/j.eclinm.2022.101454
  • Center for Countering Digital Hate. (2020) . Failure to act: How tech giants continue to defy calls to rein in vaccine misinformation.
  • Chi, Y., Daqing, H., & Jeng, W. (2020). Laypeople’s source selection in online health information-seeking process. Journal of the Association for Information Science and Technology, 71(12), 1484–1499. https://doi.org/10.1002/asi.24343
  • Chipidza, W., Akbaripourdibazar, E., Gwanzura, T., & Gatto, N. M. (2022). Topic analysis of traditional and social media news coverage of the early COVID-19 pandemic and implications for public health communication. Disaster Medicine and Public Health Preparedness, 16(5), 1881–1888. https://doi.org/10.1017/dmp.2021.65
  • Choi, J. A., & Park, S. (2021). Infodemiological study on the use of face masks during covid-19: Comparing US and Korea. Društvena istraživanja: časopis za opća društvena pitanja, 30(2), 359–378. https://doi.org/10.5559/di.30.2.09
  • Choi, S., & Powers, T. L. (2021). COVID-19: Lessons from South Korean pandemic communications strategy. International Journal of Healthcare Management, 14(1), 271–279. https://doi.org/10.1080/20479700.2020.1862997
  • Coombs, W. T. (2007). Protecting organization reputations during a crisis: The development and application of situational crisis communication theory. Corporate Reputation Review, 10(3), 163–176. https://doi.org/10.1057/palgrave.crr.1550049
  • Coombs, W. T. (2022). Situational crisis communication theory (SCCT): Refining and clarifying a cognitive-based theory of crisis communication. In W. T. Coombs & S. J. Holliday (Eds.), The handbook of crisis communication (pp. 193–204). https://doi.org/10.1002/9781119678953
  • Coombs, W. T. (2023). Ongoing crisis communication: Planning, managing, and responding (6th ed.). Sage.
  • De Sa, J., Mounier-Jack, S., & Coker, R. (2009). Risk communication and management in public health crises. Public Health, 123(10), 643–644. https://doi.org/10.1016/j.puhe.2009.07.017
  • DiMaggio, P., Nag, M., & Blei, D. (2013). Exploiting affinities between topic modeling and the sociological perspective on culture: Application to newspaper coverage of US government arts funding. Poetics, 41(6), 570–606. https://doi.org/10.1016/j.poetic.2013.08.004
  • Dsouza, V. S., Rajkhowa, P., Mallya, B. R., Raksha, D. S., Mrinalini, V., Cauvery, K., Raj, R., Toby, I., Pattanshetty, S., & Brand, H. (2023). A sentiment and content analysis of tweets on mpox stigma among the LGBTQ+ community: A cue to risk communication plan. Dialogues in Health, 2, 100095. https://doi.org/10.1016/j.dialog.2022.100095
  • Edinger, A., Valdez, D., Walsh-Buhi, E., Trueblood, J. S., Lorenzo-Luaces, L., Rutter, L. A., & Bollen, J. (2023). Misinformation and Public Health Messaging in the early stages of the mpox outbreak: Mapping the twitter narrative with deep learning. Journal of Medical Internet Research, 25, e43841. https://doi.org/10.2196/43841
  • Ennab, F., Nawaz, F. A., Narain, K., Nchasi, G., Essar, M. Y., Head, M. G., Singla, R. K., Atanasov, A. G., & Shen, B. (2022). Monkeypox outbreaks in 2022: Battling another “pandemic” of misinformation. International Journal of Public Health, 67, 1605149. https://doi.org/10.3389/ijph.2022.1605149
  • Freimuth, V. S., Stein, J. A., & Kean, T. J. (1989). Searching for health information: The Cancer information Service model. University of Pennsylvania Press.
  • Fu, K. W., Liang, H., Saroha, N., Tse, Z. T. H., Ip, P., & Fung, I. C. H. (2016). How people react to Zika virus outbreaks on Twitter? A computational content analysis. American Journal of Infection Control, 44(12), 1700–1702. https://doi.org/10.1016/j.ajic.2016.04.253
  • Geçer, E., Yıldırım, M., & Akgül, Ö. (2020). Sources of information in times of health crisis: Evidence from Turkey during COVID-19. Journal of Public Health, 30, 1–7. https://doi.org/10.1007/s10389-020-01393-x
  • Griffin, R. J., Dunwoody, S., & Neuwirth, K. (1999). Proposed model of the relationship of risk information seeking and processing to the development of preventive behaviors. Environmental Research, 80(2), S230–S245. https://doi.org/10.1006/enrs.1998.3940
  • Grimmer, J. (2015). We are all social scientists now: How big data, machine learning, and causal inference work together. PS: Political Science & Politics, 48(1), 80–83. https://doi.org/10.1017/S1049096514001784
  • Grimmer, J., & Stewart, B. M. (2013). Text as data: The promise and pitfalls of automatic content analysis methods for political texts. Political Analysis, 21(3), 267–297. https://doi.org/10.1093/pan/mps028
  • Gui, X., Kou, Y., Pine, K. H., & Chen, Y. (2017, May). Managing uncertainty: Using social media for risk assessment during a public health crisis. In Proceedings of the 2017 CHI conference on human factors in computing systems, Denver, CO, USA (pp. 4520–4533).
  • Hancher-Rauch, H. L., Britt-Spells, A., Wojtyna, A., & Standish, M. (2019). Health information seeking behavior and perceived source trustworthiness in public health students: A pilot study for improving the curriculum. Journal of Health Education Teaching, 10(1), 34–43.
  • Henry, B. (2018). Emergency response: Canadian pandemic influenza preparedness: Communications strategy. Canada Communicable Disease Report, 44(5), 106–109. https://doi.org/10.14745/ccdr.v44i05a03
  • Hofmann, T. (2001). Unsupervised learning by probabilistic latent semantic analysis. Machine Learning, 42(1/2), 177–196. https://doi.org/10.1023/A:1007617005950
  • Hubner, A. Y., & Hovick, S. R. (2020). Understanding risk information seeking and processing during an infectious disease outbreak: The case of Zika virus. Risk Analysis, 40(6), 1212–1225. https://doi.org/10.1111/risa.13456
  • Jang, K., & Baek, Y. M. (2019). When information from public health officials is untrustworthy: The use of online news, interpersonal networks, and social media during the MERS outbreak in South Korea. Health Communication, 34(9), 991–998. https://doi.org/10.1080/10410236.2018.1449552
  • Jin, X. (2020). Exploring crisis communication and information dissemination on social media: Social network analysis of hurricane irma tweets. Journal of International Crisis and Risk Communication Research, 3(2), 179–210. https://doi.org/10.30658/jicrcr.3.2.3
  • Jin, X. (2023). Political ideology and differences in seeking COVID-19 information on the internet: Examining the comprehensive model of information seeking. Online Information Review, 47(7), 1280–1301. https://doi.org/10.1108/OIR-08-2022-0436
  • Jin, Y., & Liu, B. F. (2010). The blog-mediated crisis communication model: Recommendations for responding to influential external blogs. Journal of Public Relations Research, 22(4), 429–455. https://doi.org/10.1080/10627261003801420
  • Jin, X., & Spence, P. R. (2021). Understanding crisis communication on social media with CERC: Topic model analysis of tweets about Hurricane Maria. Journal of Risk Research, 24(10), 1266–1287. https://doi.org/10.1080/13669877.2020.1848901
  • Johnson, J. D., & Meischke, H. (1993). A comprehensive model of cancer-related information seeking applied to magazines. Human Communication Research, 19(3), 343–367. https://doi.org/10.1111/j.1468-2958.1993.tb00305.x
  • Jones, S. C., Waters, L., Holland, O., Bevins, J., & Iverson, D. (2010). Developing pandemic communication strategies: Preparation without panic. Journal of Business Research, 63(2), 126–132. https://doi.org/10.1016/j.jbusres.2009.02.009
  • Kim, H. J., & Hong, H. (2022). Predicting information behaviors in the COVID-19 pandemic: Integrating the role of emotions and subjective norms into the situational theory of problem solving (STOPS) framework. Health Communication, 27(13), 1640–1649. https://doi.org/10.1080/10410236.2021.1911399
  • Kim, H. K., & Kim, Y. (2019). Risk information seeking and processing about particulate air pollution in South Korea: The roles of cultural worldview. Risk Analysis, 39(5), 1071–1087. https://doi.org/10.1111/risa.13231
  • Liew, T. M., & Lee, C. S. (2021). Examining the utility of social media in COVID-19 vaccination: unsupervised learning of 672,133 twitter posts. JMIR Public Health and Surveillance, 7(11), e29789. https://doi.org/10.2196/29789
  • Mandavilli, A. (2023). W.H.O. Declares Monkeypox Spread a Global Health Emergency. https://www.nytimes.com/2022/07/23/health/monkeypox-pandemic-who.html
  • März, J. W., Holm, S., & Biller-Andorno, N. (2022). Monkeypox, stigma and public health. The Lancet Regional Health–Europe, 23, 23. https://doi.org/10.1016/j.lanepe.2022.100536
  • McMath, B. F., & Prentice-Dunn, S. (2005). Protection motivation theory and skin cancer risk: The role of individual differences in responses to persuasive appeals. Journal of Applied Social Psychology, 35(3), 621–643. https://doi.org/10.1111/j.1559-1816.2005.tb02138.x
  • Nan, X., Iles, I. A., Yang, B., & Ma, Z. (2022). Public health messaging during the COVID-19 pandemic and beyond: Lessons from communication science. Health Communication, 37(1), 1–19. https://doi.org/10.1080/10410236.2021.1994910
  • Neely, S., Eldredge, C., & Sanders, R. (2021). Health information seeking behaviors on social media during the COVID-19 pandemic among American social networking site users: Survey study. Journal of Medical Internet Research, 23(6), e29802. https://doi.org/10.2196/29802
  • Neuwirth, K., Dunwoody, S., & Griffin, R. J. (2000). Protection motivation and risk communication. Risk Analysis, 20(5), 721–734. https://doi.org/10.1111/0272-4332.205065
  • Ng, Q. X., Yau, C. E., Lim, Y. L., Wong, L. K. T., & Liew, T. M. (2022). Public sentiment on the global outbreak of monkeypox: An unsupervised machine learning analysis of 352,182 twitter posts. Public Health, 213, 1–4. https://doi.org/10.1016/j.puhe.2022.09.008
  • Nirappil, F. (2023). WHO declares monkeypox a global health emergency as infections soar.https://www.washingtonpost.com/health/2022/07/23/monkeypox-who-global-emergency/
  • NPR. (2023, May 5). WHO ends global health emergency declaration for COVID-19.https://www.npr.org/sections/goatsandsoda/2023/05/05/1174269442/who-ends-global-health-emergency-declaration-for-covid-19
  • Ortiz-Martínez, Y., Sarmiento, J., Bonilla-Aldana, D. K., & Rodríguez-Morales, A. J. (2022). Monkeypox goes viral: Measuring the misinformation outbreak on Twitter. The Journal of Infection in Developing Countries, 16(7), 1218–1220. https://doi.org/10.3855/jidc.16907
  • Ou, M., & Ho, S. S. (2022). A meta-analysis of factors related to health information seeking: An integration from six theoretical frameworks. Communication Research, 49(4), 567–593. https://doi.org/10.1177/00936502211043024
  • Papacharissi, Z. (2016). Affective publics and structures of storytelling: Sentiment, events and mediality. Information, Communication & Society, 19(3), 307–324. https://doi.org/10.1080/1369118X.2015.1109697
  • Perez Duque, M., Ribeiro, S., Martins, J. V., Casaca, P., Leite, P. P., Tavares, M., Mansinho, K., Duque, L. M., Fernandes, C., Cordeiro, R., Borrego, M. J., Pelerito, A., de Carvalho, I. L., Núncio, S., Manageiro, V., Minetti, C., Machado, J., Haussig, J. M., Croci, R., & Vasconcelos, P.… Freitas, G. (2022). Ongoing mpox virus outbreak, Portugal, 29 April to 23 May 2022. Eurosurveillance, 27(22), 2200424. https://doi.org/10.2807/1560-7917.ES.2022.27.22.2200424
  • Phua, J., Jin, S. V., & Kim, J. J. (2017). Uses and gratifications of social networking sites for bridging and bonding social capital: A comparison of Facebook, Twitter, Instagram, and snapchat. Computers in Human Behavior, 72, 115–122. https://doi.org/10.1016/j.chb.2017.02.041
  • Rosenstock, I. M. (1974). The health belief model and preventive health behavior. Health Education Monographs, 2(4), 354–386. https://doi.org/10.1177/109019817400200405
  • Sellnow, T. L., & Seeger, M. W. (2013). Theorizing crisis communication. Wiley- Blackwell.
  • Smith, T. C. (2017). Vaccine rejection and hesitancy: A review and call to action. Open Forum Infectious Diseases,18, 4(3), ofx146. https://doi.org/10.1093/ofid/ofx146
  • Sohail, S. S. Khan, M. M. Arsalan, M. Khan, A. Siddiqui, J. Hasan, S. H. & Alam, M. A.(2021). Crawling twitter data through API: A technical/legal perspective. arXiv preprint arXiv:2105.10724.
  • Sopory, P., Day, A. M., Novak, J. M., Eckert, K., Wilkins, L., Padgett, D. R., Noyes, J. P., Barakji, F. A., Liu, J., Fowler, B. N., Guzman-Barcenas, J. B., Nagayko, A., Nickell, J. J., Donahue, D., Daniels, K., Allen, T., Alexander, N., Vanderford, M. L., & Gamhewage, G. M. (2019). Communicating uncertainty during public health emergency events: A systematic review. Review of Communication Research, 7, 67–108. https://doi.org/10.12840/ISSN.2255-4165.019
  • Tsai, M. H., & Wang, Y. (2021). Analyzing twitter data to evaluate people’s attitudes towards public health policies and events in the era of COVID-19. International Journal of Environmental Research and Public Health, 18(12), 6272. https://doi.org/10.3390/ijerph18126272
  • Turner, M. M., Rimal, R. N., Morrison, D., & Kim, H. (2006). The role of anxiety in seeking and retaining risk information: Testing the risk perception attitude framework in two studies. Human Communication Research, 32(2), 130–156. https://doi.org/10.1111/j.1468-2958.2006.00006.x
  • Vaughan, E. & Tinker, T. (2009). Effective health risk communication about pandemic influenza for vulnerable populations. American Journal of Public Health, 99(S2), S324–S332. https://doi.org/10.2105/AJPH.2009.162537
  • Vivancos, R., Anderson, C., Blomquist, P., Balasegaram, S., Bell, A., Bishop, L., Brown, C. S., Chow, Y., Edeghere, O., Florence, I., Logan, S., Manley, P., Crowe, W., McAuley, A., Shankar, A. G., Mora-Peris, B., Paranthaman, K., Prochazka, M., Ryan, C., & Riley, S.… Hopkins, S. (2022). Community transmission of monkeypox in the United Kingdom, April to May 2022. Eurosurveillance, 27(22), 2200422. https://doi.org/10.2807/1560-7917.ES.2022.27.22.2200422
  • Walter, D., Ophir, Y., Lokmanoglu, A. D., & Pruden, M. L. (2022). Vaccine discourse in white nationalist online communication: A mixed-methods computational approach. Social Science & Medicine, 298, 114859. https://doi.org/10.1016/j.socscimed.2022.114859
  • Wang, H., d’Abreu de Paulo, K. J., Gültzow, T., Zimmermann, H. M., & Jonas, K. J. (2022). Perceived monkeypox concern and risk among Men Who Have Sex with Men: Evidence and perspectives from the Netherlands. Tropical Medicine and Infectious Disease, 7(10), 293. https://doi.org/10.3390/tropicalmed7100293
  • Weeks, B. E., Friedenberg, L. M., Southwell, B. G., & Slater, J. S. (2012). Behavioral consequences of conflict-oriented health news coverage: The 2009 mammography guideline controversy and online information seeking. Health Communication, 27(2), 158–166. https://doi.org/10.1080/10410236.2011.571757
  • Winters, M., Malik, A. A., Omer, S. B., & Harapan, H. (2022). Attitudes towards Monkeypox vaccination and predictors of vaccination intentions among the US general public. PLoS One, 17(12), e0278622. https://doi.org/10.1371/journal.pone.0278622
  • Witte, K. (1992). Putting the fear back into fear appeals: The extended parallel process model. Communication Monographs, 59(4), 329–349. https://doi.org/10.1080/03637759209376276
  • Witte, K. (1996). Predicting risk behaviors: Development and validation of a diagnostic scale. Journal of Health Communication, 1(4), 317–342. https://doi.org/10.1080/108107396127988
  • World Health Organization. (2022, July 23). WHO Director-General’s statement at the press conference following IHR Emergency Committee regarding the multi-country outbreak of monkeypox - 23 July 2022. https://www.who.int/director-general/speeches/detail/who-director-general-s-statement-on-the-press-conference-following-IHR-emergency-committee-regarding-the-multi–country-outbreak-of-monkeypox–23-july-2022
  • World Health Organization. (2023). About WHO. https://www.who.int/about
  • Zhang, R. N., Bazarova, N., & Reddy, M. (2021, May). Distress disclosure across social media platforms during the COVID-19 pandemic: Untangling the effects of platforms, affordances, and audiences. In Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems, Yokohama, Japan (pp. 1–15).

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.