Abstract
Vaccines are an essential public health resource for disease containment and reduction of associated mortality rates. With the emergence of COVID-19, public debates on the themes of vaccines and vaccination processes became important topics on diverse media and social networking platforms. In this article, our objective was to identify and reflect on the emotions evoked in the Brazilian public with respect to the COVID-19 vaccine during 2020 and 2021 on Facebook. To achieve this, we used the Crowdtangle graphical interface to extract complete copies of posts made by public Facebook profiles during this timeframe, from which a random sample of 1,067 posts was selected for analysis. Identification of emotions was performed using the Human-Machine Interaction Network on Emotion (HUMAINE) descriptors as a baseline reference. Emotions were then grouped into categories following Core Affect Model guidelines. Data analysis and interpretation indicated a prevalence of positive emotions such as trust, interest, and hope directed toward vaccines in the Brazilian domestic scenario. Negative emotions such as worry and disapproval were also expressed, albeit in reference to contextual issues (for example, the spread of COVID-19, delays in vaccine access, and the emergence of new variants) and public figures, such as the President of Brazil.
References
Ahmed, S. (2014). The cultural politics of emotion. Edinburgh University Press. https://doi.org/10.4324/9780203700372
Link DOI | Link Google Scholar
Aman, S., & Szpakowicz, S. (2007). Identifying expressions of emotion in text. In V. Matousek, & P. Mautner (Eds.), Text, speech and dialogue. Lecture notes in computer Science (pp. 196-205). Springer. https://doi.org/10.1007/978-3-540-74628-7_27
Link DOI | Link Google Scholar
Avaaz & Sociedade Brasileira de Imunizações (Ed.) (2019). As fake news estão nos deixando doentes?
Link Google Scholar
Benevenuto, F., Ribeiro, F., & Araújo, M. (2015). Métodos para análise de sentimentos em mídias sociais. In Short course in the Brazilian Symposium on Multimedia and the Web (Webmedia) (pp. 1-30). https://bit.ly/3eiD3bF
Link Google Scholar
Berger, J., & Milkman, K.L. (2012). What makes online content viral? Journal of Marketing Research, 49(2), 192-205. https://doi.org/10.1509/jmr.10.0353
Link DOI | Link Google Scholar
Bok, K., Sitar, S., Graham, B.S., & Mascola, J.R. (2021). Accelerated COVID-19 vaccine development: Milestones, lessons, and prospects. Immunity, 54(8), 1636-1651. https://doi.org/10.1016/j.immuni.2021.07.017
Link DOI | Link Google Scholar
Calhoun, C. (2008). Putting emotions in their place. In V. Ruggiero, & N. Montagna (Eds.), Social movements: A read (pp. 289-301). Routledge student readers. https://bit.ly/3IFXhqP
Link Google Scholar
Chou, W.S., & Budenz, A. (2020). Considering emotion in COVID-19 vaccine communication: Addressing vaccine hesitancy and fostering vaccine confidence. Health Commun, 35(14), 1718-1722. https://doi.org/10.1080/10410236.2020.1838096
Link DOI | Link Google Scholar
Clarke, S., Hoggett, P., & Thompson, S. (2006). Emotion, politics and society. Palgrave Macmillan. https://doi.org/10.1057/9780230627895
Link DOI | Link Google Scholar
Costa, T., & Silva, E.A. (2022). Narrativas antivacinas e a crise de confiança em algumas instituições. Revista Eletrônica de Comunicação, Informação e Inovação em Saúde, 16(2), 281-297. https://doi.org/10.29397/reciis.v16i2.3229
Link DOI | Link Google Scholar
Devillers, L., Vidrascu, L., & Lamel, L. (2005). Challenges in real-life emotion annotation and machine learning based detection. Neural Netw, 8(4), 407-22. https://doi.org/10.1016/j.neunet.2005.03.007
Link DOI | Link Google Scholar
Douglas-Cowie, E., Cowie, R., Sneddon, I., Cox, C., Lowry, O., McRorie, M., Martin, J., Devillers, L., Abrilian, S., Batliner, A., Amir, N., & Karpouzis, K. (2007). The HUMAINE database: Addressing the collection and annotation of naturalistic and induced emotional data. In A.C.R. Paiva, R. Prada, & R.W. Picard (Eds.), Affective computing and intelligent interaction (pp. 488-500). Springer. https://doi.org/10.1007/978-3-540-74889-2_43
Link DOI | Link Google Scholar
Duarte, T.B. (2020). Ignoring scientific advice during the Covid-19 pandemic: Bolsonaro’s actions and discourse. Tapuya: Latin American Science, Technology and Society, 3(1), 288-291. https://doi.org/10.1080/25729861.2020.1767492
Link DOI | Link Google Scholar
Dubé, E., Vivion, M., & MacDonald, N.E. (2015). Vaccine hesitancy, vaccine refusal and the anti-vaccine movement: Influence, impact and implications. Expert Rev Vaccines. 14(1), 99-117. https://doi.org/10.1586/14760584.2015.964212
Link DOI | Link Google Scholar
Gallup (Ed.) (2019). Wellcome Global Monitor 2018. https://bit.ly/3SvLmR3
Link Google Scholar
Gonçalves, G., Rocha, A., & Paes, A. (2022). Analisando as emoções dos tweets relacionados à Covid-19 no Rio de Janeiro. In L. Villas, T.H. Silva, D.L. Guidoni, G. Pereira-Rocha-Filho & V. Mota (Eds.), 2022: Anais do VI Workshop de Computação Urbana (pp. 210-223). SBC. https://doi.org/10.5753/courb.2022.223557
Link DOI | Link Google Scholar
Gonçalves, P., Araújo, M., Benevenuto, F., & Cha, M. (2013). Comparing and combining sentiment analysis methods. In M. Muthukrishnan, A. El Abbadi & B. Krishnamurthy (Ed.), COSN’13: Proceedings of the first ACM conference on online social networks (pp. 27-38). Association for Computing Machinery. https://doi.org/10.1145/2512938.2512951
Link DOI | Link Google Scholar
Greyling, T., & Rossouw, S. (2022). Positive attitudes towards COVID-19 vaccines: A cross-country analysis. PLoS ONE, 17(3), 1-25. https://doi.org/10.1371/journal.pone.0264994
Link DOI | Link Google Scholar
Hu, T., Wang, S., Luo, W., Zhang, M., Huang, X., Yan, Y., Liu, R., Ly, K., Kacker, V., She, B., & Li, Z. (2021). Revealing public opinion towards COVID-19 vaccines with Twitter Data in the United States: A spatiotemporal perspective. J Med Internet Res, 23(9), 1-17. https://doi.org/10.1101/2021.06.02.21258233
Link DOI | Link Google Scholar
Kennedy, J. (2020). Vaccine hesitancy: A growing concern. Pediatric Drugs, 22(2), 105-111. https://doi.org/10.1007/s40272-020-00385-4
Link DOI | Link Google Scholar
Kwok, S.W.H., Vadde S.K., & Wang, G. (2021). Tweet topics and sentiments relating to COVID-19 vaccination among australian Twitter users: Machine learning analysis. J Med Internet Res., 23(5), 1-16. https://doi.org/10.2196/26953
Link DOI | Link Google Scholar
Mahyoob, M., Algaraady, J., Alrahiali, M., & Alblwi, A. (2022). Sentiment analysis of public tweets towards the emergence of SARS-CoV-2 Omicron variant: A social media analytics framework. engineering, Technology & Applied Science Research, 12(3), 8525-8531. https://doi.org/10.48084/etasr.4865
Link DOI | Link Google Scholar
Martin, J.C., Caridakis, G., Devillers, L., Karpouzis, K., & Abrilian, S. (2009). Manual annotation and automatic image processing of multimodal emotional behaviors: Validating the annotation of TV interviews. Pers Ubiquit Comput, 13, 69-76. https://doi.org/10.1007/s00779-007-0167-y
Link DOI | Link Google Scholar
Massarani, L., Leal, T., Waltz, I., & Medeiros, A. (2021). Infodemia, desinformação e vacinas: a circulação de conteúdos em redes sociais antes e depois da COVID-19. Liinc Em Revista, 17(1), 1-23. https://doi.org/10.18617/liinc.v17i1.5689
Link DOI | Link Google Scholar
Milani, L.R.N., & Busato, I.M.S. (2021). Causas e consequências da redução da cobertura vacinal no Brasil. Revista de Saúde Pública do Paraná, 4(2), 157-171. https://doi.org/10.32811/25954482-2021v4n2p157
Link DOI | Link Google Scholar
Monselise, M., Chang, C.H., Ferreira, G., Yang, R., & Yang, C.C. (2021). Topics and sentiments of public concerns regarding COVID-19 vaccines: Social media trend analysis. J Med Internet Res, 23(10), 1-20. https://doi.org/10.2196/30765
Link DOI | Link Google Scholar
Nobre, R.K.M., & Guerra, L.D.S. (2021). Recusa e hesitação vacinal e os seus efeitos para os sistemas universais de saúde. Journal of Management & Primary Health Care, 12(spec), 1-2. https://doi.org/10.14295/jmphc.v12.1086
Link DOI | Link Google Scholar
Obeica, I.C.O., & Martins, D.M.S. (2022). Análise de sentimentos em tweets: Um estudo de caso sobre a opinião das pessoas em relação a vacina em tempos da pandemia do COVID-19. Caderno de estudos em Engenharia de Software. 4(1), 1-21. https://bit.ly/3DSfzEA
Link Google Scholar
Oliveira, T., Quinan, R., & Toth, J.P. (2020). Antivacina, fosfoetanolamina e Mineral Miracle Solution (MMS): mapeamento de fake sciences ligadas à saúde no Facebook. Revista Eletrônica de Comunicação, Informação & Inovação em Saúde, 14(1), 90-111. https://doi.org/10.29397/reciis.v14i1.1988
Link DOI | Link Google Scholar
Orr, D., Baram-Tsabari, A., & Landsman, K. (2016). Social media as a platform for health-related public debates and discussions: The Polio vaccine on Facebook. Isr J Health Policy Res, 5(34), 1-11. https://doi.org/10.1186/s13584-016-0093-4
Link DOI | Link Google Scholar
Papacharissi, Z. (2014) Affective publics: Sentiment, technology and politics. Oxford University Press. https://doi.org/10.1093/acprof:oso/9780199999736.001.0001
Link DOI | Link Google Scholar
Penteado, C.L.C, Ferreira, M.A.S., Pereira, M.A., & Chaves, J.M.S. (2021). #Vacinar ou não, eis a questão! As emoções na disputa discursiva sobre a aprovação das vacinas contra a Covid-19 no Twitter. Política & Sociedade, 20(49), 104-133. https://doi.org/10.5007/2175-7984.2021.85145
Link DOI | Link Google Scholar
Potkay, A. (2007). The story of joy: from the Bible to late Romanticism. Cambridge University Press.
Link Google Scholar
Rahmanti, A.R., Chien, C.H., Nursetyo, A.A., Husnayain, A., Wiratama, B.S., Fuad, A., Yang, H.C., & Li, Y.C.J. (2022). Social media sentiment analysis to monitor the performance of vaccination coverage during the early phase of the national COVID-19 vaccine rollout. Computer Methods and Programs in Biomedicine, 221, 106838. https://doi.org/10.1016/j.cmpb.2022.106838
Link DOI | Link Google Scholar
Rezende, C.B., & Coelho, M.C. (2010). Antropologia das emoções. Editora FGV. https://bit.ly/42nIj1V
Link Google Scholar
Rodas, C.M., Barros, S.E.T., Souza, R.A.S., & Vidotti, S.A.B.G. (2022). Análise de sentimentos sobre as vacinas contra Covid-19: Um estudo com algoritmo de machine learning em postagens no twitter. Rev. Saúde Digital Tec. Educ., 7(3), 24-44. https://bit.ly/3RdNNoT
Link Google Scholar
Rowe, S., Massarani, L., Gonçalves, W., & Luz, R. (2023). Emotion in informal learning as mediated action: Cultural, interpersonal and personal lenses. International Journal of Studies in Education and Science, 4(1), 73-99. https://doi.org/10.46328/ijses.50
Link DOI | Link Google Scholar
Russell, J.A. (2003). Core affect and the psychological construction of emotion. Psychological Review, 110(1), 145-172. https://doi.org/10.1037/0033-295X.110.1.145
Link DOI | Link Google Scholar
Russell, J.A. (2009). Emotion, core affect, and psychological construction. Cognition & Emotion, 23(7), 1259-1283. https://doi.org/10.1080/02699930902809375
Link DOI | Link Google Scholar
Santos, F.C., & Cypriano, C.P. (2014). Redes sociais, redes de sociabilidade. Revista Brasileira de Ciências Sociais, 29(85), 63-78. https://doi.org/10.1590/S0102-69092014000200005
Link DOI | Link Google Scholar
Schröder, M., Pirker, H., & Lamolle, M. (2006). First suggestions for an emotion annotation and representation language. In Proceedings of LREC 2006 Workshop on corpora for research on emotion and affect (pp. 88-92). https://bit.ly/3r2fruE
Link Google Scholar
Serrano-Puche, J. (2016). Internet and emotions: New trends in an emerging field of research. [Internet y emociones: nuevas tendencias en un campo de investigación emergente]. Comunicar, 46, 19-26. https://doi.org/10.3916/C46-2016-02
Link DOI | Link Google Scholar
Siegert, I., Böck, R., & Wendemuth, A. (2014). Inter-rater reliability for emotion annotation in human-computer interaction: Comparison and methodological improvements. J Multimodal user interfaces, 8(1), 17-28. https://doi.org/10.1007/s12193-013-0129-9
Link DOI | Link Google Scholar
We Are Social (Ed.) (2022). Digital 2022 global overview report. Hootsuite. https://bit.ly/3DQEKaC
Link Google Scholar
World Health Organization (Ed.) (2019). Ten threats to global health in 2019. https://bit.ly/3xMP6Vd
Link Google Scholar
Geilson Fernandes-de-Oliveira, Oswaldo Cruz Foundation (Brazil)
