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• W4287840906 abstract "<sec> <title>BACKGROUND</title> Since the onset of the COVID-19 pandemic, vaccines have been an important topic in public discourse. The discussions around vaccines are polarized as some see them as an important measure to end the pandemic, and others are hesitant or find them harmful. A significant portion of these discussions takes place openly on social media platforms. This allows us to closely monitor the opinions of different groups and their changes over time. </sec> <sec> <title>OBJECTIVE</title> This study investigates posts related to COVID-19 vaccines on Twitter and focuses on those which have negative stances toward vaccines. We look into the evolution of the percentage of negative tweets over time. We also examine the different topics discussed in these tweets, in order to understand the concerns and discussion points of those holding a negative stance toward the vaccines. </sec> <sec> <title>METHODS</title> A dataset of 16,713,238 English tweets related to COVID-19 vaccines was collected covering the period from March 1, 2020, to July 31, 2021. We used the Scikit-learn Python library to apply a support vector machine (SVM) classifier to identify the tweets with a negative stance toward the COVID-19 vaccines. A total of 5,163 tweets were used to train the classifier, out of which a subset of 2,484 tweets was manually annotated by us and made publicly available. We used the BERTtopic model to extract and investigate the topics discussed within the negative tweets and how they changed over time. </sec> <sec> <title>RESULTS</title> We show that the negativity with respect to COVID-19 vaccines has decreased over time along with the vaccine roll-outs. We identify 37 topics of discussion and present their respective importance over time. We show that popular topics consist of conspiratorial discussions such as 5G towers and microchips, but also contain legitimate concerns around vaccination safety and side effects as well as concerns about policies. The most prevalent topic among vaccine-hesitant tweets is related to the use of mRNA and fears about speculated negative effects on our DNA. </sec> <sec> <title>CONCLUSIONS</title> Hesitancy toward vaccines existed prior to COVID-19. However, given the dimension and circumstances surrounding the COVID-19 pandemic, some new areas of hesitancy and negativity toward the COVID-19 vaccines have arisen, for example, whether there has been enough time for them to be properly tested. There is also an unprecedented amount of conspiracy theories associated with them. Our study shows that even unpopular opinions or conspiracy theories can become widespread when paired with a widely popular discussion topic such as COVID-19 vaccines. Understanding the concerns and the discussed topics and how they change over time is essential for policymakers and public health authorities to provide better and in-time information and policies, to facilitate vaccination of the population in future similar crises. </sec>" @default.
• W4287840906 created "2022-07-26" @default.
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• W4287840906 date "2022-07-21" @default.
• W4287840906 modified "2023-09-27" @default.
• W4287840906 title "Vaccine Discourse on Twitter During the COVID-19 Pandemic (Preprint)" @default.
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• W4287840906 doi "https://doi.org/10.2196/preprints.41319" @default.
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