论文标题
COVID-19社交媒体的Infodemic
The COVID-19 Social Media Infodemic
论文作者
论文摘要
我们通过在Twitter，Instagram，YouTube，Reddit和GAB上进行大量数据分析来解决有关COVID-19的信息的扩散。我们分析了对COVID-19主题的参与度和兴趣，并为每个平台及其用户在全球范围内的演讲演变提供了差异评估。我们将信息传播的流行模型拟合，这些模型表征了每个社交媒体平台的基本繁殖编号$ R_0 $。此外，我们表征了从可疑来源传播的信息，在每个平台中发现不同的错误信息。但是，来自可靠和可疑来源的信息并不呈现不同的传播模式。最后，我们提供了依赖平台的谣言放大的数值估计。
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 numbers $R_0$ for each social media platform. Moreover, we characterize 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.
