CNR-ISC, Rome, Italy.
Università Ca' Foscari di Venezia, Venice, Italy.
Sci Rep. 2020 Oct 6;10(1):16598. doi: 10.1038/s41598-020-73510-5.
We address the diffusion of information about the COVID-19 with a massive data analysis on Twitter, Instagram, YouTube, Reddit and Gab. We analyze engagement and interest in the COVID-19 topic and provide a differential assessment on the evolution of the discourse on a global scale for each platform and their users. We fit information spreading with epidemic models characterizing the basic reproduction number [Formula: see text] for each social media platform. Moreover, we identify information spreading from questionable sources, finding different volumes of misinformation in each platform. However, information from both reliable and questionable sources do not present different spreading patterns. Finally, we provide platform-dependent numerical estimates of rumors' amplification.
我们利用对 Twitter、Instagram、YouTube、Reddit 和 Gab 上的大量数据进行的分析来研究有关 COVID-19 的信息传播。我们分析了对 COVID-19 主题的参与度和兴趣,并对每个平台及其用户的全球范围内的话语演变进行了差异评估。我们根据社交媒体平台的基本再生数 [Formula: see text] 对信息传播进行拟合。此外,我们还从可疑来源中发现了不同数量的错误信息。然而,可靠和可疑来源的信息并没有呈现出不同的传播模式。最后,我们提供了依赖于平台的谣言放大的数值估计。