The COVID-19 social media infodemic

Abstract

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.

Figure 1

Upper panel: activity (likes, comments, reposts, etc.) distribution for each social media. Middle panel: most discussed topics about COVID-19 on each social media. Lower panel: cumulative number of content (posts, tweets, videos, etc.) produced from the 1st of January to the 14th of February. Due to the Twitter API limitations in gathering past data, the first data point for Twitter is dated January 27th.

Figure 2

Growth of the number of authors versus time. Time is expressed in number of days since 1st January 2020 (day 1). Shaded areas represents [5%, 95%] estimates of the models obtained via bootstrapping least square estimates of the EXP model (upper panels) and of the SIR model (lower panels). For details the SIR and the EXP model, see SI.

Figure 3

Upper panels: plot of the cumulative number of posts referring to questionable sources versus the cumulative number of posts referring to reliable sources. Lower panel: plot of the cumulative number of engagements relatives to questionable sources versus the cumulative number of engagements relative to reliable sources. Notice that a linear behavior indicates that the time evolution of questionable posts/engagements is just a re-scaled version of the time evolution of reliable posts/engagements. Each plot indicates the regression coefficients $\rho$, representing the ratio among the volumes of questionable and reliable posts (${\rho }^{\mathit{post}}$) and engagements (${\rho }^{\mathit{eng}}$). In more popular social media, the number of questionable posts represents a small fraction of the reliable ones; same thing happens in Reddit. Among less popular social media, a peculiar effect is observed in Gab: while the volume of questionable posts is just the $\sim 70\%$ of the volume of reliable ones, the volume of engagements for questionable posts is $\sim 3$ times bigger than the volume for reliable ones. Further details concerning the regression coefficients are reported in Methods.