Mis-tweeting communication: a Vaccine Hesitancy analysis among twitter users in Italy
Main Article Content
Vaccine Hesitancy, Twitter, Social Media, Public Health, Vaccination, COVID-19, SARS-CoV-2, anti-vax
Background and aim: A previously unseen body of scientific knowledge of varying quality has been produced during the ongoing COVID-19 pandemic. It has proven extremely difficult to navigate for experts and laymen alike, originating a phenomenon described as “Infodemic”, a breeding ground for misinformation. This has a potential impact on vaccine hesitancy that must be considered in a situation where efficient vaccination campaigns are of the greatest importance. We aimed at describing the polarization and volumes of Italian language tweets in the months before and after the start of the vaccination campaign in Italy.
Methods: Tweets were sampled in the October 2020-January 2021 period. The characteristics of the dataset were analyzed after manual annotation as Anti-Vax, Pro-Vax and Neutral, which allowed for the definition of a polarity score for each tweet.
Results: Based on the annotated tweets, we could identify 29.6% of the 2,538 unique users as anti-Vax and 12.1% as pro-Vax, with a strong disagreement in annotation in 7.1% of the tweets. We observed a change in the proportion of retweets to anti-Vax and pro-Vax messages after the start of the vaccination campaign in Italy. Although the most shared tweets are those of opposite orientation, the most retweeted users are moderately polarized.
Conclusions: The disagreement on the manual classification of tweets highlights a potential risk for misinterpretation of tweets among the general population. Our study reinforces the need to focus Public Health’s attention on the new social media with the aim of increasing vaccine confidence, especially in the context of the current pandemic.
2. Ten Health Issues WHO Will Tackle This Year. Available online: https://www.who.int/news-room/spotlight/ten-threats-to-global-health-in-2019 (accessed on 25 May 2021).
3. MacDonald, N.E.; SAGE Working Group on Vaccine Hesitancy Vaccine Hesitancy: Definition, Scope and Determinants. Vaccine 2015, 33, 4161–4164.
4. Sallam, M. COVID-19 Vaccine Hesitancy Worldwide: A Concise Systematic Review of Vaccine Acceptance Rates. Vaccines (Basel) 2021, 9.
5. Neumann-Böhme, S.; Varghese, N.E.; Sabat, I.; Barros, P.P.; Brouwer, W.; van Exel, J.; Schreyögg, J.; Stargardt, T. Once We Have It, Will We Use It? A European Survey on Willingness to Be Vaccinated against COVID-19. Eur J Health Econ 2020, 21, 977–982.
6. Salali, G.D.; Uysal, M.S. COVID-19 Vaccine Hesitancy Is Associated with Beliefs on the Origin of the Novel Coronavirus in the UK and Turkey. Psychol Med 2020, 1–3.
7. Lazarus, J.V.; Ratzan, S.C.; Palayew, A.; Gostin, L.O.; Larson, H.J.; Rabin, K.; Kimball, S.; El-Mohandes, A. A Global Survey of Potential Acceptance of a COVID-19 Vaccine. Nature Medicine 2021, 27, 225–228.
8. Sallam, M.; Dababseh, D.; Eid, H.; Al-Mahzoum, K.; Al-Haidar, A.; Taim, D.; Yaseen, A.; Ababneh, N.A.; Bakri, F.G.; Mahafzah, A. High Rates of COVID-19 Vaccine Hesitancy and Its Association with Conspiracy Beliefs: A Study in Jordan and Kuwait among Other Arab Countries. Vaccines (Basel) 2021, 9.
9. Reno C, Maietti E, Fantini MP, Savoia E, Manzoli L, Montalti M, Gori D. Enhancing COVID-19 Vaccines Acceptance: Results from a Survey on Vaccine Hesitancy in Northern Italy. Vaccines. 2021; 9(4):378. https://doi.org/10.3390/vaccines9040378
10. Britton T, Ball F, Trapman P. A mathematical model reveals the influence of population heterogeneity on herd immunity to SARS-CoV-2. Science (80- ). 2020;369(6505):846–9.
11. Billah MA, Miah MM, Khan MN. Reproductive number of coronavirus: A systematic review and meta-analysis based on global level evidence. PLoS One. 2020;15(11 November):1–17. Available at: http://dx.doi.org/10.1371/journal.pone.0242128
12. Puri, N.; Coomes, E.A.; Haghbayan, H.; Gunaratne, K. Social Media and Vaccine Hesitancy: New Updates for the Era of COVID-19 and Globalized Infectious Diseases. Hum Vaccin Immunother 2020, 16, 2586–2593.
13. Blankenship EB, Goff ME, Yin J, Tse ZTH, Fu K-W, Liang H, Saroha N, Fung ICH. Sentiment, contents, and retweets: a study of two vaccine-related twitter datasets. Perm J. 2018;22:17–138. doi:10.7812/TPP/17-138.
14. Basch CH, Zybert P, Reeves R, Basch CE. What do popular YouTube TM videos say about vaccines? Child Care Health Dev. 2017;43(4):499. doi:10.1111/cch.12401.
15. Schmidt, A.L.; Zollo, F.; Scala, A.; Betsch, C.; Quattrociocchi, W. Polarization of the Vaccination Debate on Facebook. Vaccine 2018, 36, 3606–3612.
16. Betsch, C.; Renkewitz, F.; Betsch, T.; Ulshöfer, C. The Influence of Vaccine-Critical Websites on Perceiving Vaccination Risks. J Health Psychol 2010, 15, 446–455.
17. Nan, X.; Madden, K. HPV Vaccine Information in the Blogosphere: How Positive and Negative Blogs Influence Vaccine-Related Risk Perceptions, Attitudes, and Behavioral Intentions. Health Commun 2012, 27, 829–836.
18. Ahmed, N.; Quinn, S.C.; Hancock, G.R.; Freimuth, V.S.; Jamison, A. Social Media Use and Influenza Vaccine Uptake among White and African American Adults. Vaccine 2018, 36, 7556–7561.
19. Bhattacharyya, S.; Vutha, A.; Bauch, C.T. The Impact of Rare but Severe Vaccine Adverse Events on Behaviour-Disease Dynamics: A Network Model. Scientific Reports 2019, 9, 7164.
20. UNICRI, United Nations Interregional Crime and Justice Research Institute. Available online: http://www.unicri.it/index.php/News/COVID19-Disinformation-Malicious-Use-Social-Media-Terrorists-Organizedcrime (accessed on 25 May 2021).
21. David A. Broniatowski, Amelia M. Jamison, SiHua Qi, Lulwah AlKulaib, Tao Chen, Adrian Benton, Sandra C. Quinn, and Mark Dredze Weaponized Health Communication: Twitter Bots and Russian Trolls Amplify the Vaccine Debate. American Journal of Public Health 2018 , 108, 1378-1384, https://doi.org/10.2105/AJPH.2018.304567
22. Keith Gunaratne, Eric A. Coomes, Hourmazd Haghbayan, Temporal trends in anti-vaccine discourse on Twitter, Vaccine 2019, 35, 4867-4871
23. Johnson, N.F.; Velásquez, N.; Restrepo, N.J.; Leahy, R.; Gabriel, N.; El Oud, S.; Zheng, M.; Manrique, P.; Wuchty, S.; Lupu, Y. The Online Competition between Pro- and Anti-Vaccination Views. Nature 2020, 582, 230–233.
24. Germani, F.; Biller-Andorno, N. The Anti-Vaccination Infodemic on Social Media: A Behavioral Analysis. PLOS ONE 2021, 16, e0247642.
25. Gori, D.; Reno, C.; Remondini, D.; Durazzi, F.; Fantini, M.P. Are We Ready for the Arrival of the New COVID-19 Vaccinations? Great Promises and Unknown Challenges Still to Come. Vaccines 2021, 9, 173.
26. Piedrahita-Valdés, H.; Piedrahita-Castillo, D.; Bermejo-Higuera, J.; Guillem-Saiz, P.; Bermejo-Higuera, J.R.; Guillem-Saiz, J.; Sicilia-Montalvo, J.A.; Machío-Regidor, F. Vaccine Hesitancy on Social Media: Sentiment Analysis from June 2011 to April 2019. Vaccines 2021, 9, 28.
27. Albalawi, Y.; Nikolov, N.S.; Buckley, J. Trustworthy Health-Related Tweets on Social Media in Saudi Arabia: Tweet Metadata Analysis. Journal of Medical Internet Research 2019, 21, e14731.
28. Pierri, F.; Piccardi, C.; Ceri, S. Topology Comparison of Twitter Diffusion Networks Effectively Reveals Misleading Information. Sci Rep 2020, 10.
29. Shahi, G.K.; Dirkson, A.; Majchrzak, T.A. An Exploratory Study of COVID-19 Misinformation on Twitter. Online Soc Netw Media 2021, 22, 100104.
30. Giese H, Neth H, Moussaïd M, Betsch C, Gaissmaier W. The echo in flu-vaccination echo chambers: selective attention trumps social influence. Vaccine. 2019. doi:10.1016/j.vaccine.2019.11.038.
31. Broniatowski DA, Hilyard KM, Dredze M. Effective vaccine communication during the disneyland measles outbreak. Vaccine. 2016;34(28):3225–28. doi:10.1016/j.vaccine.2016.04.044.
32. European Medicine Agency, Signal assessment report on embolic and thrombotic events (SMQ) with COVID-19 Vaccine (ChAdOx1-S [recombinant]) – COVID-19 Vaccine AstraZeneca (Other viral vaccines). Available online: https://www.ema.europa.eu/en/documents/prac-recommendation/signal-assessment-report-embolic-thrombotic-events-smq-covid-19-vaccine-chadox1-s-recombinant-covid_en.pdf (accessed on 25 May 2021)
33. Hulsen, T.; Jamuar, S.S.; Moody, A.R.; Karnes, J.H.; Varga, O.; Hedensted, S.; Spreafico, R.; Hafler, D.A.; McKinney, E.F. From Big Data to Precision Medicine. Front. Med. 2019, 6.
34. Cossin, S.; Thiébaut, R.; Section Editors for the IMIA Yearbook Section on Public Health and Epidemiology Informatics Public Health and Epidemiology Informatics: Recent Research Trends Moving toward Public Health Data Science. Yearb Med Inform 2020, 29, 231–234.
35. Eysenbach, G. Infodemiology and Infoveillance: Tracking Online Health Information and Cyberbehavior for Public Health. American Journal of Preventive Medicine 2011, 40, S154–S158.