论文标题
疫苗错误信息的动态和触发因素
Dynamics and triggers of misinformation on vaccines
论文作者
论文摘要
COVID-19大流行激发了人们对在线误解的普遍性的重新关注，无论是否有意，都强调了与个人对误解的传播和对与健康相关的受试者的传播相关的潜在风险。在这项研究中，我们分析了在各种社交媒体平台（Facebook，Instagram，Twitter，YouTube）之间进行了6年（2016-2021）的意大利疫苗辩论，涵盖了所有主要新闻来源 - 既有疑问又可靠。我们首先使用新闻生产时间序列的符号转移熵分析来动态确定哪些可疑或可靠的来源类别可因果驱动疫苗的议程。然后，利用能够基于传达的立场和讨论主题来准确对疫苗相关的内容进行准确分类的深度学习模型，我们通过新闻来源评估了对各种主题的关注，从而促进相反的观点并比较结果的用户参与度。 Aside from providing valuable resources for further investigation of vaccine-related misinformation, particularly in a language (Italian) that receives less attention in scientific research compared to languages like English, our study uncovers misinformation not as a parasite of the news ecosystem that merely opposes the perspectives offered by mainstream media, but as an autonomous force capable of even overwhelming the production of vaccine-related content from the latter.尽管与可靠的消息来源相比，在可疑来源的参与度明显更高的情况下，错误信息的普遍性显而易见，但我们的发现强调了一致和彻底的亲vax覆盖范围的重要性。这对于解决最敏感的主题尤为重要，在这种主题中，错误信息传播的风险和可能加剧所涉及用户疫苗的负面态度的风险更高。
The Covid-19 pandemic has sparked renewed attention on the prevalence of misinformation online, whether intentional or not, underscoring the potential risks posed to individuals' quality of life associated with the dissemination of misconceptions and enduring myths on health-related subjects. In this study, we analyze 6 years (2016-2021) of Italian vaccine debate across diverse social media platforms (Facebook, Instagram, Twitter, YouTube), encompassing all major news sources - both questionable and reliable. We first use the symbolic transfer entropy analysis of news production time-series to dynamically determine which category of sources, questionable or reliable, causally drives the agenda on vaccines. Then, leveraging deep learning models capable to accurately classify vaccine-related content based on the conveyed stance and discussed topic, respectively, we evaluate the focus on various topics by news sources promoting opposing views and compare the resulting user engagement. Aside from providing valuable resources for further investigation of vaccine-related misinformation, particularly in a language (Italian) that receives less attention in scientific research compared to languages like English, our study uncovers misinformation not as a parasite of the news ecosystem that merely opposes the perspectives offered by mainstream media, but as an autonomous force capable of even overwhelming the production of vaccine-related content from the latter. While the pervasiveness of misinformation is evident in the significantly higher engagement of questionable sources compared to reliable ones, our findings underscore the importance of consistent and thorough pro-vax coverage. This is especially crucial in addressing the most sensitive topics where the risk of misinformation spreading and potentially exacerbating negative attitudes toward vaccines among the users involved is higher.
