YOUTUBE AS A SOURCE OF INFORMATION ABOUT UNPROVEN DRUGS FOR COVID-19: the role of the mainstream media and recommendation algorithms in promoting misinformation

Soares, F., Salgueiro, I., Bonoto, C., & Vinhas, O. (2022). YOUTUBE AS A SOURCE OF INFORMATION ABOUT UNPROVEN DRUGS FOR COVID-19: the role of the mainstream media and recommendation algorithms in promoting misinformation. Brazilian Journalism Research, 18(3), 462–491. https://doi.org/10.25200/BJR.v18n3.2022.1536

Résumé

ABSTRACT - In this study, we address how YouTube videos promote misinformation about hydroxychloroquine in Brazil. We follow two research questions. RQ1: How is pro-hydroxychloroquine content propagated on YouTube? RQ2: How does YouTube’s recommendation system suggest videos about hydroxychloroquine on the platform? We use mixed methods (content analysis and social network analysis) to analyze 751 YouTube videos. We found that most pro-HCQ videos in our dataset are posted by mainstream media channels (RQ1) and that YouTube was more likely to recommend pro-HCQ videos than anti-HCQ videos (RQ2). Consequently, the Brazilian mainstream media and YouTube’s algorithms fueled the spread of pro-HCQ content.

RESUMO – Neste estudo, abordamos como os vídeos no YouTube promovem desinformação sobre a hidroxicloroquina no Brasil. Seguimos duas questões de pesquisa. RQ1: Como o conteúdo pró-hidroxicloroquina é propagado no YouTube? RQ2: Como o sistema de recomendação do YouTube sugere vídeos sobre hidroxicloroquina na plataforma? Usamos métodos mistos (análise de conteúdo e análise de redes sociais) para analisar 751 vídeos do YouTube. Descobrimos que a maioria dos vídeos pró-HCQ em nosso conjunto de dados foi postado pelos principais canais de mídia (RQ1) e que o YouTube era mais propenso a recomendar vídeos pró-HCQ do que vídeos anti-HCQ (RQ2). Consequentemente, a imprensa tradicional brasileira e os algoritmos do YouTube fomentaram a disseminação de conteúdo pró-HCQ.

RESUMEN – En este estudio, abordamos cómo videos en YouTube promueven desinformación sobre la hidroxicloroquina en Brasil. Seguimos dos preguntas de investigación. RQ1: ¿Cómo se propaga el contenido pro-hidroxicloroquina en YouTube? RQ2: ¿Cómo el sistema de recomendaciones de YouTube sugiere videos sobre hidroxicloroquina en la plataforma? Utilizamos métodos mixtos (análisis de contenido y análisis de redes sociales) para analizar 751 videos de YouTube. Descubrimos que la mayoría de los videos pro-HCQ en nuestro conjunto de datos son publicados por los principales canales de medios de comunicación (RQ1) y que era más probable que YouTube recomendara videos pro-HCQ que videos anti-HCQ (RQ2). En consecuencia, los principales medios de comunicación brasileños y los algoritmos de YouTube impulsaron la difusión de contenido pro-HCQ.

https://doi.org/10.25200/BJR.v18n3.2022.1536

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Références

Abul-Fottouh, D., Song, M. Y., & Gruzd, A. (2020). Examining algorithmic biases in YouTube’s recommendations of vaccine videos. International Journal of Medical Informatics, 140(104175), 1–6 . DOI: 10.1016/j.ijmedinf.2020.104175

Alves, M. (2022). As flutuações de longo prazo da polarização no Brasil – análise de compartilhamento de informações políticas entre 2011 e 2019. Revista Dados, 66(2),1–45. DOI: 10.1590/dados.2023.66.2.287

Araújo, R., & Oliveira, T. A. (2020). Desinformação e mensagens sobre a hidroxicloroquina no Twitter: da pressão política à disputa científica. Atoz: novas práticas em informação e conhecimento, 9(2),196–205. DOI: 10.5380/atoz.v9i2.75929

Barbosa, B., Fávero, B., Ely, D., & Barbosa, J. (2021, February 26). Impulsionados pela imprensa, médicos que desinformam sobre Covid-19 somam 30 mi de visualizações no YouTube. Radar Aos Fatos. Retrieved from www.aosfatos.org/noticias/impulsionados-pela-imprensa-medicos-que-desinformam-sobre-covid-19-somam-30-mi-de-visualizacoes-no-youtube/

Bardin, L. (1977). Análise de conteúdo. PUF.

Benkler, Y., Faris, R., & Roberts, H. (2018). Network Propaganda: Manipulation, disinformation, and radicalization in American politics. Oxford University Press.

Bennett, W., & Livingston, S. (2018). The disinformation order: Disruptive communication and the decline of democratic institutions. European Journal of Communication, 33(2), 122–139. DOI: 10.1177/0267323118760317

Casarões, G., Magalhães, D. (2021). The hydroxychloroquine alliance: how far-right leaders and alt-science preachers came together to promote a miracle drug. Revista de Administração Pública, 55(1), 197–214. DOI: 10.1590/0034-761220200556

Cohen, J. A. (1960). A Coefficient of Agreement for Nominal Scales. Educational and Psychological Measurement, 20(1), 37–46. DOI: 10.1177/001316446002000104

Fetzer, J. H. (2004). Disinformation: The Use of False Information. Minds and Machines, 14(2), 231–240. DOI: 10.1023/B:MIND.0000021683.28604.5b

Floridi, L. (2011). The philosophy of information. Oxford University Press.

Flynn, D. J., Nyhan, B., & Reifler, J. (2017). The Nature and Origins of Misperceptions: Understanding False and Unsupported Beliefs About Politics. Advances in Political Psychology, 38(1), 127–150. DOI: 10.1111/pops.12394

Fonseca, N. (2021, April 16). YouTube remove vídeos que indicam o uso de cloroquina e ivermectina contra Covid. CNN Brasil. Retrieved from www.cnnbrasil.com.br/tecnologia/youtube-remove-videos-que-indicam-o-uso-de-cloroquina-e-ivermectina-contra-covid/

Hosseinmardi, H., Ghasemian, A., Clauset, A., Mobius, M., Rothschild, D. M., & Watts, D. J. (2021). Examining the consumption of radical content on YouTube. Proceedings of the National Academy of Sciences, 118(32). DOI: 10.1073/pnas.2101967118

Jack, C. (2017). Lexicon of Lies: Terms for Problematic Information. Data & Society Research Institute.

JASP Team. (2020). JASP (Version 0.14.1) [computer software].

Kaiser, J., & Rauchfleisch, A. (2020). Birds of a Feather Get Recommended Together: Algorithmic Homophily in YouTube’s Channel Recommendations in the United States and Germany. Social Media + Society, 6(4), 1–15. DOI: 10.1177/2056305120969914

Krackhardt, D., & Stern, R. N. (1988). Informal Networks and Organizational Crises: An Experimental Simulation. Social Psychology Quarterly, 51(2), 123–140. DOI: 10.2307/2786835

Landis, J. R., & Koch, G. G. (1977). The measurement of observer agreement for categorical data. Biometrics, 33(1), 159–174. DOI: 10.2307/2529310

Machado, C. C. V., Dourado, D. A., Santos, J. G., & Santos, N. (2020). Ciência Contaminada: Analisando o contágio de desinformação sobre coronavírus via YouTube. Laut. Retrieved from https://laut.org.br/ciencia-contaminada.pdf

Madathil, K. C., Rivera-Rodriguez, A. J., Greenstein, J. S, & Gramopadhye, A K. (2015). Healthcare information on YouTube: A systematic review. Health Informatics Journal, 21(3), 173–194. DOI: 10.1177/1460458213512220

Mozilla. (2019, n.d.). How healthy is the internet? Retrieved from https://internethealthreport.org/2019/

Newman, N., Fletcher, R., Robertson, C. T., Eddy, K., & Nielsen, R. K. (2022). Reuters Institute Digital News Report 2022. Reuters Institute, Oxford University.

O’Callaghan, D., Greene, D., Conway, M., Carthy, J., & Cunningham, P. (2014). Down the (White) Rabbit Hole: The Extreme Right and Online Recommender Systems. Social Science Computer Review, 33(4), 459–478. DOI: 10.1177/0894439314555329

O’Donovan, C. (2019, February 22). YouTube Just Demonetized Anti-Vax Channels. BuzzFeed News. Retrieved from www.buzzfeednews.com/article/carolineodonovan/youtube-just-demonetized-anti-vax-channels

Pariser, E. (2011). The filter bubble: What the Internet is hiding from you. Penguin.

Ramos, T. B., Bokehi, L. C., Bokehi, R. C., Pinheiro, T. S., Oliveira, E. B., Torres, R. S. G., Bokehi, J. R., Calil-Elias, S., & Castilho, S. R. (2020). YouTube as a source of information on chloroquine and hydroxychloroquine during the COVID-19 pandemic. Journal of Science Communication, 19(07), 1–19. DOI: 10.22323/2.19070206

Recuero, R., Soares, F. B., & Zago, G. (2021). Polarização, Hiperpartidarismo e Câmaras de Eco: Como circula a Desinformação sobre Covid-19 no Twitter. Contracampo, 40(1), 1–17. DOI: 10.22409/contracampo.v40i1.45611

Ricard, J., & Medeiros, J. (2020). Using misinformation as a politic al weapon: COVID - 19 and Bolsonaro in Brazil. Harvard Kennedy School (HKS) Misinformation Review, 1(2), 1-6. DOI: 10.37016/mr-2020-013

Rieder, B. (2015). YouTube Data Tools (Version 1.22) [software]. Available from https://tools.digitalmethods.net/netvizz/youtube/

Röchert, D., Weitzel, M., & Ross, B. (2020). The homogeneity of right-wing populist and radical content in YouTube recommendations. Proceedings of the International Conference on Social Media and Society. Association for Computing Machinery. DOI: 10.1145/3400806.3400835

Song, M. Y., & Gruzd, A. (2017). Examining Sentiments and Popularity of Pro- and Anti-Vaccination Videos on YouTube. Proceedings of the 8th International Conference on Social Media & Society. Association for Computing Machinery. DOI: 10.1145/3097286.3097303

Soares, F. B., Recuero, R., & Zago, G. (2019). Asymmetric Polarization on Twitter and the 2018 Brazilian Presidential Elections. Proceedings of the 10th International Conference on Social Media and Society. Association for Computing Machinery. DOI: 10.1145/3328529.3328546

Soares, F. B., Bonoto, C., Viegas, P., Salgueiro, I., & Recuero, R. (2020). Disputas discursivas e desinformação no Instagram sobre o uso da hidroxicloroquina como tratamento para o Covid-19. Proceedings of the Congresso Brasileiro de Ciências da Comunicação. UFBA. Retrieved from https://portalintercom.org.br/anais/nacional2020/resumos/R15-0550-1.pdf

Soares, F. B., & Recuero, R. (2021). How the Mainstream Media Help to Spread Disinformation about Covid-19. M/C Journal, 24(1). DOI: 10.5204/mcj.2735

Soares, F. B., Viegas, P., Bonoto, C., & Recuero, R. (2021). Covid-19, desinformação e Facebook: circulação de URLs sobre a hidroxicloroquina em páginas e grupos públicos. Galáxia, 46(46), 1–24. DOI: 10.1590/1982-2553202151423

Spagnuolo, S., & Orrico, A. (2020, March 2023). Coronavírus: interesse sobre cloroquina disparou após vídeo de Bolsonaro. Núcleo. Retrieved from https://nucleo.jor.br/redes/2020-03-23-cloroquina-bolsonaro-video-coronavirus

Sunstein, C. R. (2001). Republic.com. Princeton University Press.

Tangcharoensathien, V., Calleja, N., Nguyen, T., Purnat, T., D’Agostino, M., Garcia-Saiso, S., Landry, M., Rashidian, A., Hamilton, C., AbdAllah, A., Ghiga, I., Hill, A., Hougendobler, D., van Andel, J., Nunn, M., Brooks, I., Sacco, P. L., De Domenico, M., Mai, P., Gruzd, A., Alaphilippe, A., & Briand, S. (2020). Framework for Managing the COVID-19 Infodemic: Methods and Results of an Online Crowdsourced WHO Technical Consultation. J Med Internet Res, 22(6). DOI: 10.2196/19659

Tokojima Machado, D. F., de Siqueira, A. F., & Gitahy, L. (2020). Natural Stings: Selling Distrust About Vaccines on Brazilian YouTube. Frontiers in Communication, 5, 2–9. DOI: 10.3389/fcomm.2020.577941

Tsfati, Y., Boomgaarden, H. G., Strömbäck, J., Vliegenthart, R., Damstra A., & Lindgren, E. (2020). Causes and consequences of mainstream media dissemination of fake news: literature review and synthesis. Annals of the International Communication Association, 44(2), 157–173. DOI: 10.1080/23808985.2020.1759443

Wardle, C. (2019). Understanding Information Disorder. First Draft.

Wasserman, S., & Faust, K. (1994). Social Network Analysis. Cambridge University Press.

Watmough, S. P. (2021). Jair Bolsonaro: Far-Right Firebrand and Cheerleader for Dictatorship. European Center for Populism Studies. Retrieved from www.populismstudies.org/jair-bolsonaro-far-right-firebrand-and-cheerleader-for-dictatorship/

Watts, D. J., & Strogatz, S. H. (1998). Collective dynamics of ‘small-world’ networks. Nature, 393, 440-442. DOI:10.1038/30918

YouTube Team. (2019, January 25). Continuing our work to improve recommendations on YouTube. YouTube Official Blog. Retrieved from https://blog.youtube/news-and-events/continuing-our-work-to-improve

Zhou, R., Khemmarat, S., Gao, L., Wan, J., & Zhang, J. (2016). How YouTube videos are discovered and its impact on video views. Multimed Tools Appl, 75, 6035–6058. DOI: 10.1007/s11042-015-3206-0

Zimmerman, D. W. (2004). A note on preliminary tests of equality of variances. The British Journal of Mathematical and Statistical Psychology, 57, 173–181. DOI: 10.1348/000711004849222

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YOUTUBE AS A SOURCE OF INFORMATION ABOUT UNPROVEN DRUGS FOR COVID-19: the role of the mainstream media and recommendation algorithms in promoting misinformation

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