ArticleEuropean journal of public health2020
How do Twitter users react to TV broadcasts dedicated to vaccines in Italy?
Article in European journal of public health, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
5 citing papers in PubMed, 1 synthesis or guideline pooled it, 9 citations in OpenAlex.
- Multi-perspectives systematic review on the applications of sentiment analysis for vaccine hesitancy.Computers in biology and medicine · 2021Pooled it
- Spreading of misinformation on mass media and digital platforms regarding vaccines. A systematic scoping review on stakeholders, policymakers, and sentiments/behavior of Italian consumers.Human vaccines & immunotherapeutics · 2023Article
- Emergency Medical Services Calls Analysis for Trend Prediction during Epidemic Outbreaks: Interrupted Time Series Analysis on 2020-2021 COVID-19 Epidemic in Lazio, Italy.International journal of environmental research and public health · 2022Article
- How the Italian Twitter Conversation on Vaccines Changed During the First Phase of the Pandemic: A Mixed-Method Analysis.Frontiers in public health · 2022Article
- Media Data and Vaccine Hesitancy: Scoping Review.JMIR infodemiologyArticle
Corrections and comments
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Authors and funding
10 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundSocial 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)].
methodsTweets 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.
resultsWe 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).
conclusionsTwitter 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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.