Electronic International Standard Serial Number (EISSN)
1873-2518
abstract
Objectives: Characterize the public debate and discourse about vaccines during the covid-19 vaccination programmes. Methods: We performed a manual content analysis of a sample of English-written Twitter posts that included the word vaccine and its derivatives. We categorized 7 variables pertaining to the content of the posts, and classified the type of user that published the post and the number of retweets. Then, the patterns of association between these variables were further explored. Results: Among the tweets with negative tone towards vaccines, 33% display negationist discourses, 29% protest or defiance discourses, 13% discuss the pandemic management measures and yet another 13% of these tweets display a scientific discourse. Research results, vaccination data and practical information are more associated to positive tone towards vaccines, while news relate to neutral tone. The users that received more retweets were media accounts and journalists, followed by government accounts and scientific organizations related to the government. Tweets displaying preventive messages received more retweets in average. The discourses most associated with objective information are the preventive, institutional, medical-scientific, and those about the different measures to manage the pandemic. On the other hand, the most subjective tweets are those with negationist, antinegationist and protest discourses. Conclusions: Although there is a non-negligible proportion of tweets that are directly opposed to vaccines, also an important part of vaccine-negative content takes the form of protest discourses, criticisms towards government actions as well as towards the measures to tackle the pandemic. Therefore, negative discourses during the pandemic included serious vaccine hesitancy cases. Moreover, they were not only fuelled by distrust in science, but also and very importantly they were connected to dissatisfaction towards the public management of the pandemic.
Classification
keywords
covid-19; discourse; misinformation; social media; twitter; vaccination