How do Twitter users react to TV broadcasts dedicated to vaccines in Italy?

Autor:	Gesualdo F; Predictive and Preventive Medicine Research Unit, Multifactorial and Complex Disease Research Area, Bambino Gesù Children's Hospital, IRCCS, Rome, Italy., D'Ambrosio A; Department of Public Health and Pediatric Sciences, University of Turin, Turin, Italy., Agricola E; Predictive and Preventive Medicine Research Unit, Multifactorial and Complex Disease Research Area, Bambino Gesù Children's Hospital, IRCCS, Rome, Italy., Russo L; Predictive and Preventive Medicine Research Unit, Multifactorial and Complex Disease Research Area, Bambino Gesù Children's Hospital, IRCCS, Rome, Italy., Campagna I; Predictive and Preventive Medicine Research Unit, Multifactorial and Complex Disease Research Area, Bambino Gesù Children's Hospital, IRCCS, Rome, Italy., Ferretti B; Predictive and Preventive Medicine Research Unit, Multifactorial and Complex Disease Research Area, Bambino Gesù Children's Hospital, IRCCS, Rome, Italy., Pandolfi E; Predictive and Preventive Medicine Research Unit, Multifactorial and Complex Disease Research Area, Bambino Gesù Children's Hospital, IRCCS, Rome, Italy., Cristoforetti M; Information and Communication Technology Department, Fondazione Bruno Kessler, Trento, Italy., Tozzi AE; Predictive and Preventive Medicine Research Unit, Multifactorial and Complex Disease Research Area, Bambino Gesù Children's Hospital, IRCCS, Rome, Italy., Rizzo C; Predictive and Preventive Medicine Research Unit, Multifactorial and Complex Disease Research Area, Bambino Gesù Children's Hospital, IRCCS, Rome, Italy.
Jazyk:	angličtina
Zdroj:	European journal of public health [Eur J Public Health] 2020 Jun 01; Vol. 30 (3), pp. 510-515.
DOI:	10.1093/eurpub/ckaa022
Abstrakt:	Background: Social media monitoring during TV broadcasts dedicated to vaccines can provide information on vaccine confidence. We analyzed the sentiment of tweets published in reaction to two TV broadcasts in Italy dedicated to vaccines, one based on scientific evidence [Presadiretta (PD)] and one including anti-vaccine personalities [Virus (VS)]. Methods: Tweets about vaccines published in an 8-day period centred on each of the two TV broadcasts were classified by sentiment. Differences in tweets' and users' characteristics between the two broadcasts were tested through Poisson, quasi-Poisson or logistic univariate regression. We investigated the association between users' characteristics and sentiment through univariate quasi-binomial logistic regression. Results: We downloaded 12 180 tweets pertinent to vaccines, published by 5447 users; 276 users tweeted during both broadcasts. Sentiment was positive in 50.4% of tweets, negative in 37.7% and neutral in 10.1% (remaining tweets were unclear or questions). The positive/negative ratio was higher for VS compared to PD (6.96 vs. 4.24, P<0.001). Positive sentiment was associated to the user's number of followers (OR 1.68, P<0.001), friends (OR 1.83, P<0.001) and published tweets (OR 1.46, P<0.001) and to being a recurrent user (OR 3.26, P<0.001). Conclusions: Twitter users were highly reactive to TV broadcasts dedicated to vaccines. Sentiment was mainly positive, especially among very active users. Displaying anti-vaccine positions on TV elicited a positive sentiment on Twitter. Listening to social media during TV shows dedicated to vaccines can provide a diverse set of data that can be exploited by public health institutions to inform tailored vaccine communication initiatives. (© The Author(s) 2020. Published by Oxford University Press on behalf of the European Public Health Association.)
Databáze:	MEDLINE
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