Citizen participation in Twitter: Anti-vaccine controversies in times of COVID-19

Carrasco-Polaino, Rafael, Martín-Cárdaba, Miguel-Ángel and Villar-Cirujano, Ernesto Citizen participation in Twitter: Anti-vaccine controversies in times of COVID-19. Comunicar, 2021, vol. 29, n. 69, pp. 21-31. [Journal article (Paginated)]

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English abstract

Twitter has transformed into one of the main platforms for citizen engagement today. However, even though previous studies have focused on opinions about vaccines in general or about specific vaccines, opinions towards COVID-19 vaccines on Twitter have not been researched to date. The objective of this research is, by using social network analysis and language processing tools, to examine the degree to which the opinions and interactions present on Twitter are favorable or unfavorable towards the main COVID-19 vaccines. In addition, the relevance of each of the vaccines is studied, as well as their level of controversy. Likewise, the present study investigates, for the first time, the conversation from different perspectives including the content and also the participants, by analyzing in detail the verified accounts and using tools for the detection of bots. In global terms, the results from verified accounts show a moderate favorability towards the COVID-19 vaccines, the most accepted being those of Oxford-AstraZeneca, Pfizer, Moderna, and Sputnik V. On the other hand, the vaccine that attracts the most attention is the Russian Sputnik V, which is also the most controversial, behind those developed in China. Finally, verified users are shown to be relevant agents in the conversation due to their greater capacity for dissemination and reach, while the presence of bots is practically non-existent.

Spanish abstract

Twitter se ha transformado en una de las principales plataformas de participación ciudadana hoy en día. Sin embargo, aun cuando estudios similares previos se han centrado en la opinión sobre las vacunas en general o sobre otras vacunas específicas, hasta la fecha no se han investigado las opiniones hacia las vacunas contra la COVID-19 en Twitter. El objetivo de esta investigación es, mediante el uso de herramientas de análisis de redes sociales y de herramientas de procesamiento del lenguaje, examinar el grado en el que las opiniones e interacciones presentes en Twitter son favorables o no hacia las principales vacunas de la COVID-19. Además, se estudia la relevancia de cada una de las principales vacunas, así como su nivel de controversia (polemicidad). Igualmente, el presente estudio investiga por primera vez la conversación no solo desde el punto de vista del contenido, sino también de los participantes que la integran, analizando en detalle las cuentas verificadas y empleando herramientas para la detección de bots. En términos globales, los resultados muestran una moderada favorabilidad hacia las vacunas de la COVID-19, siendo las más aceptadas las de Oxford-AstraZeneca, Pfizer y Moderna, y la de Sputnik V en el caso concreto de las cuentas verificadas. Por otro lado, la vacuna que más atención acapara es la rusa Sputnik V, que es además la más polémica por detrás de las de origen chino. Por último, los usuarios verificados se muestran como agentes relevantes de la conversación por su mayor capacidad de difusión y alcance, mientras que la presencia de bots es prácticamente inexistente.

Item type: Journal article (Paginated)
Keywords: Network analysis; quantitative analysis; misinformation; virtual communities; social media; critical thinking; Análisis de redes; análisis cuantitativo; desinformación; comunidades virtuales; redes sociales; pensamiento crítico
Subjects: B. Information use and sociology of information > BJ. Communication
G. Industry, profession and education.
G. Industry, profession and education. > GH. Education.
Depositing user: Alex Ruiz
Date deposited: 21 Dec 2021 12:02
Last modified: 21 Dec 2021 12:02
URI: http://hdl.handle.net/10760/42709

References

Andre, F.E., Booy, R., Bock, H.L., Clemens, J., Datta, S. K., John, T.J., Lee, B.W., Lolekha, S., Peltola, H., Ruff, T.A., Santosham, M., & Schmitt, H.J. (2008). Vaccination greatly reduces disease, disability, death and inequity worldwide. Bulletin of the World Health Organization, 86(2), 140-146. https://doi.org/10.2471/BLT.07.040089

Auger, G.A. (2013). Fostering democracy through social media: Evaluating diametrically opposed nonprofit advocacy organizations’ use of Facebook, Twitter, and YouTube. Public Relations Review, 39(4), 369-376. https://doi.org/10.1016/j.pubrev.2013.07.013

Bello-Orgaz, G., Hernandez-Castro, J., & Camacho, D. (2017). Detecting discussion communities on vaccination in twitter. Future Generation Computer Systems, 66, 125-136. https://doi.org/10.1016/j.future.2016.06.032

Bertin, P., Nera, K., & Delouvée, S. (2020). Conspiracy beliefs, rejection of vaccination, and support for hydroxychloroquine: A conceptual replication-extension in the COVID-19 pandemic context. Frontiers in psychology, 11, 1-9. https://doi.org/10.3389/fpsyg.2020.565128

Bosch, T. (2017). Twitter activism and youth in South Africa: The case of #RhodesMustFall. Information, Communication & Society, 20(2), 221-232. https://doi.org/10.1080/1369118X.2016.1162829

Botometer (Ed.) (2020). Botometer® by OSoMe. FAQ. https://bit.ly/3bGEPh8

Brand, E., & Gomez, H. (2006). Análisis de redes sociales como metodología de investigación. Elementos básicos y aplicación. Repositorio Institucional Universidad de Antioquia. https://bit.ly/3npVOdi

Broniatowski, D.A., Jamison, A.M., Qi, S., AlKulaib, L., Chen, T., Benton, A., Quinn, S.C., & Dredze, M. (2018). Weaponized health communication: Twitter bots and russian trolls amplify the vaccine debate. American Journal of Public Health, 108(10), 1378-1384. https://doi.org/10.2105/AJPH.2018.304567

Burnap, P., Gibson, R., Sloan, L., Southern, R., & Williams, M. (2016). 140 characters to victory? Using Twitter to predict the UK 2015 general election. Electoral Studies, 41, 230-233. https://doi.org/10.1016/j.electstud.2015.11.017

Callaway, E. (2020). Russia announces positive COVID-vaccine results from controversial trial. Nature. https://doi.org/10.1038/d41586-020-03209-0

Centro de Investigaciones Sociológicas (CIS) (Ed.) (2021). Barómetro de febrero 2021. https://bit.ly/37LyfFj

Colleoni, E., Rozza, A., & Arvidsson, A. (2014). Echo chamber or public sphere? Predicting political orientation and measuring political homophily in Twitter using big data. Journal of Communication, 64(2), 317-332. https://doi.org/10.1111/jcom.12084

Cuesta-Cambra, U., Martínez-Martínez, L., & Niño-González, J.I. (2019). Análisis de la información pro vacunas y anti vacunas en redes sociales e internet. Patrones visuales y emocionales. Profesional de la Información, 28(2), e280217. https://doi.org/10.3145/epi.2019.mar.17

Denia, E. (2020). The impact of science communication on Twitter: The case of Neil deGrasse Tyson. [El impacto del discurso científico en Twitter: El caso de Neil deGrasse Tyson]. Comunicar, 65, 21-30. https://doi.org/10.3916/C65-2020-02

Dixon, G., & Clarke, C. (2013). The effect of falsely balanced reporting of the autism-vaccine controversy on vaccine safety perceptions and behavioral intentions. Health Education Research, 28(2), 352-359. https://doi.org/10.1093/her/cys110

Dror, A.A., Eisenbach, N., Taiber, S., Morozov, N.G., Mizrachi, M., Zigron, A., Srouji, S., & Sela, E. (2020). Vaccine hesitancy: the next challenge in the fight against COVID-19. European Journal of Epidemiology, 35, 775-779. https://doi.org/10.1007/s10654-020-00671-y

Dubé, E., Vivion, M., & MacDonald, N.E. (2015). Vaccine hesitancy, vaccine refusal and the anti-vaccine movement: Influence, impact and implications. Expert Review of Vaccines, 14(1), 99-117. https://doi.org/10.1586/14760584.2015.964212

Fauziyyah, A. (2020). Analisis sentimen pandemi Covid19 pada streaming Twitter dengan text mining Python. Jurnal Ilmiah SINUS, 18(2), 31-42. https://doi.org/10.30646/sinus.v18i2.491

Flaherty, D.K. (2011). The vaccine-autism connection: A public health crisis caused by unethical medical practices and fraudulent science. Annals of Pharmacotherapy, 45(10), 1302-1304. https://doi.org/10.1345/aph.1Q318

François, G., Duclos, P., Margolis, H., Lavanchy, D., Siegrist, C.A., Meheus, A., Lambert, P.H., Emiroglu, N., Badur, S., & Van-Damme, P. (2005). Vaccine safety controversies and the future of vaccination programs. The Pediatric Infectious Disease Journal, 24(11), 953-961. https://doi.org/10.1097/01.inf.0000183853.16113.a6

Friedrich, M.J. (2019). WHO’s Top Health Threats for 2019. JAMA, 321(11). https://doi.org/10.1001/jama.2019.1934

Gintova, M. (2019). Understanding government social media users: An analysis of interactions on immigration, refugees and citizenship Canada Twitter and Facebook. Government Information Quarterly, 36(4), 101388. https://doi.org/10.1016/j.giq.2019.06.005

Graells-Garrido, E., Baeza-Yates, R., & Lalmas, M. (2019). How representative is an abortion debate on Twitter? In P. Boldi, B. Foucault-Welles, K, Kinder-Kurlanda, & C. Wilson (Eds.), Proceedings of the 10th ACM Conference on Web Science - WebSci ’19. (pp. 133-134). Association for Computing Machinery https://doi.org/10.1145/3292522.3326057

Hansen, D., Shneiderman, B., & Smith, M.A. (2010). Analyzing social media networks with NodeXL: Insights from a connected world. Graduate Journal of Social Science. https://doi.org/10.1016/B978-0-12-382229-1.00011-4

Himelboim, I., Xiao, X., Lee, D.K.L., Wang, M.Y., & Borah, P. (2020). A social networks approach to understanding vaccine conversations on Twitter: Network clusters, sentiment, and certainty in HPV social networks. Health Communication, 35(5), 607-615. https://doi.org/10.1080/10410236.2019.1573446

Hornsey, M.J., Harris, E.A., & Fielding, K.S. (2018). The psychological roots of anti-vaccination attitudes: A 24-nation investigation. Health Psychology, 37(4), 307-315. https://doi.org/10.1037/hea0000586

Jolley, D., & Douglas, K.M. (2014). The effects of anti-vaccine conspiracy theories on vaccination intentions. PLoS ONE, 9(2), 89177. https://doi.org/10.1371/journal.pone.0089177

Kouzy, R., Abi-Jaoude, J., Kraitem, A., El-Alam, M.B., Karam, B., Adib, E., Zarka, J., Traboulsi, C., Akl, E., & Baddour, K. (2020). Coronavirus goes viral: Quantifying the COVID-19 misinformation epidemic on Twitter. Cureus, 12(3). https://doi.org/10.7759/cureus.7255

López-Rico, C.M., González-Esteban, J.L., & Hernández-Martínez, A. (2020). Consumo de información en redes sociales durante la crisis de la COVID-19 en España. Revista de Comunicación y Salud, 10(2), 461-481. https://doi.org/10.35669/rcys.2020.10(2).461-481

Loria, S. (2020). TextBlob: Simplified text processing (0.16.0). https://bit.ly/3knzFL8

Manfredi-Sánchez, J., Amado-Suárez, A., & Waisbord, S. (2021). Presidential Twitter in the face of COVID-19: Between populism and pop politics. [Twitter presidencial ante la COVID-19: Entre el populismo y la política pop]. Comunicar, 66, 83-94. https://doi.org/10.3916/C66-2021-07

McKnight, P.E., & Najab, J. (2010). Mann?Whitney U Test. In I.B. Weiner, & W.E. Craighead (Eds.), The Corsini Encyclopedia of Psychology. John Wiley & Sons. https://doi.org/10.1002/9780470479216.corpsy0524

Meyer, S.B., Violette, R., Aggarwal, R., Simeoni, M., MacDougall, H., & Waite, N. (2019). Vaccine hesitancy and Web 2.0: Exploring how attitudes and beliefs about influenza vaccination are exchanged in online threaded user comments. Vaccine, 37(13), 1769-1774. https://doi.org/10.1016/j.vaccine.2019.02.028

Micu, A., Micu, A.E., Geru, M., & Lixandroiu, R.C. (2017). Analyzing user sentiment in social media: Implications for online marketing strategy. Psychology & Marketing, 34(12), 1094-1100. https://doi.org/10.1002/mar.21049

Milani, E., Weitkamp, E., & Webb, P. (2020). The visual vaccine debate on Twitter: A social network analysis. Media and Communication, 8(2), 364–375. https://doi.org/10.17645/mac.v8i2.2847

Oliphant, T.E. (2007). Python for scientific computing. Computing in Science & Engineering, 9(3), 10-20. https://doi.org/10.1109/MCSE.2007.58

Organización de Naciones Unidas (Ed.) (2020). Covid-19. Impact of the Pandemic on Trade and Development. https://bit.ly/2R4D0Eu

Organización Mundial de la Salud (Ed.) (2020a). Cronología de la respuesta de la OMS a la COVID-19. https://bit.ly/3qV2GA7

Organización Mundial de la Salud (Ed.) (2020b). Draft landscape and tracker of COVID-19 candidate vaccines. https://bit.ly/3snMdF6

Ostertagova, E., Ostertag, O., & Kovác, J. (2014). Methodology and application of the Kruskal-Wallis test. Applied Mechanics and Materials, 611, 115-120. https://doi.org/10.4028/www.scientific.net/AMM.611.115

Poland, G.A., & Spier, R. (2010). Fear, misinformation, and innumerates: How the Wakefield paper, the press, and advocacy groups damaged the public health. Vaccine, 28(12), 2361-2362. https://doi.org/10.1016/j.vaccine.2010.02.052

Puente, S.N., Maceiras, S.D., & Romero, D.F. (2021). Twitter activism and ethical witnessing: Possibilities and challenges of feminist politics against gender-based violence. Social Science Computer Review, 39(2), 295-311. https://doi.org/10.1177/0894439319864898

Puri, N., Coomes, E.A., Haghbayan, H., & Gunaratne, K. (2020). Social media and vaccine hesitancy: New updates for the era of COVID-19 and globalized infectious diseases. Human Vaccines and Immunotherapeutics, 16(11), 1-8. https://doi.org/10.1080/21645515.2020.1780846

Schmidt, A.L., Zollo, F., Scala, A., Betsch, C., & Quattrociocchi, W. (2018). Polarization of the vaccination debate on Facebook. Vaccine, 36(25), 3606-3612. https://doi.org/10.1016/j.vaccine.2018.05.040

Serrano-Contreras, I.J., García-Marín, J., & Luengo, O.G. (2020). Measuring online political dialogue: Does polarization trigger more deliberation? Media and Communication, 8(4), 63-72. https://doi.org/10.17645/mac.v8i4.3149

Spier, R.E. (2001). Perception of risk of vaccine adverse events: A historical perspective. Vaccine, 20(1), 78-84. https://doi.org/10.1016/S0264-410X(01)00306-1

Subrahmanian, V., Azaria, A., Durst, S., Kagan, V., Galstyan, A., Lerman, K., Zhu, L., Ferrara, E., Flammini, A., & Menczer, F. (2016). The DARPA Twitter bot challenge. Computer, 49(6), 38-46. https://doi.org/10.1109/MC.2016.183

Sued-Palmeiro, G.E., & Cebral-Loureda, M. (2020). Voces autorizadas en Twitter durante la pandemia de COVID-19: Actores, léxico y sentimientos como marco interpretativo para usuarios ordinarios. Revista de Comunicación y Salud, 10(2), 549-568. https://doi.org/10.35669/rcys.2020.10(2).549-568

The American Journal of Managed Care (AJMC) (Ed.) (2020). A Timeline of COVID-19 Developments in 2020. https://bit.ly/3xZI7qk

Tomeny, T.S., Vargo, C.J., & El-Toukhy, S. (2017). Geographic and demographic correlates of autism-related anti-vaccine beliefs on Twitter, 2009-15. Social Science and Medicine, 191, 168-175. https://doi.org/10.1016/j.socscimed.2017.08.041

Tornos-Inza, E. (2020). Tasa de interacción (engagement) en Twitter. Related: Marketing. https://bit.ly/3aSs9Vj

Twitter (Ed.) (2021). Acerca de las cuentas verificadas de Twitter. https://bit.ly/3dGRmUF

Vu, H.T., Do, H.V., Seo, H., & Liu, Y. (2020). Who leads the conversation on climate change? A study of a global network of NGOS on Twitter. Environmental Communication, 14(4), 450-464. https://doi.org/10.1080/17524032.2019.1687099

World Economic Forum (Ed.) (2021). More people now plan to get a COVID-19 vaccine than in December. https://bit.ly/3r6cQ1f

Xiong, Y., Cho, M., & Boatwright, B. (2019). Hashtag activism and message frames among social movement organizations: Semantic network analysis and thematic analysis of Twitter during the #MeToo movement. Public Relations Review, 45(1), 10-23. https://doi.org/10.1016/j.pubrev.2018.10.014

Yang, S., Quan-Haase, A., & Rannenberg, K. (2017). The changing public sphere on Twitter: Network structure, elites and topics of the #righttobeforgotten. New Media & Society, 19(12), 1983-2002. https://doi.org/10.1177/1461444816651409

Yelin, D., Wirtheim, E., Vetter, P., Kalil, A.C., Bruchfeld, J., Runold, M., Guaraldi, G., Mussini, C., Gudiol, C., Pujol, M., Bandera, A., Scudeller, L., Paul, M., Kaiser, L., & Leibovici, L. (2020). Long-term consequences of COVID-19: Research needs. The Lancet Infectious Diseases, 20(10), 1115-1117. https://doi.org/10.1016/S1473-3099(20)30701-5

YouGov (Ed.). (2021). COVID-19 Public Monitor. COVID-19 Public Monitor. https://yougov.co.uk/COVID-19

Zimmer, C., Corum, J., & Wee, S.L. (2021, January 11). Coronavirus vaccine tracker. The New York Times. https://nyti.ms/2NCtMxI


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