Gori Davide, Durazzi Francesco, Montalti Marco, Di Valerio Zeno, Reno Chiara, Fantini Maria Pia, Remondini Daniel
Department of Biomedical and Neuromotor Sciences, University of Bologna.
Department of Physics, University of Bologna.
Acta Biomed. 2021 Oct 5;92(S6):e2021416. doi: 10.23750/abm.v92iS6.12251.
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.
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.
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.
在持续的新冠疫情期间，产生了一批质量参差不齐、此前未见的科学知识。事实证明，无论是专家还是普通民众，都极难梳理这些知识，由此产生了一种被称为“信息疫情”的现象，这是错误信息的滋生地。在高效的疫苗接种运动至关重要的情况下，这可能会对疫苗犹豫产生影响，必须予以考虑。我们旨在描述意大利疫苗接种运动开始前后几个月意大利语推文的两极分化情况和数量。
在2020年10月至2021年1月期间对推文进行采样。在将数据集手动标注为反疫苗、支持疫苗和中性后，对其特征进行分析，这使得能够为每条推文定义一个极性分数。
根据标注的推文，我们可以确定在2538名独特用户中，29.6%为反疫苗用户，12.1%为支持疫苗用户，7.1%的推文在标注上存在强烈分歧。我们观察到意大利疫苗接种运动开始后，转发反疫苗和支持疫苗信息的比例发生了变化。尽管分享最多的推文是那些立场相反的，但转发最多的用户两极分化程度适中。结论：推文手动分类上的分歧凸显了普通民众对推文误解的潜在风险。我们的研究强化了公共卫生部门需要关注新社交媒体的必要性，以提高疫苗信心，尤其是在当前疫情背景下。
