Followers do not dictate the virality of news outlets on social media

Abstract

Initially conceived for entertainment, social media platforms have profoundly transformed the dissemination of information and consequently reshaped the dynamics of agenda-setting. In this scenario, understanding the factors that capture audience attention and drive viral content is crucial. Employing Gibrat's Law, which posits that an entity's growth rate is unrelated to its size, we examine the engagement growth dynamics of news outlets on social media. Our analysis encloses the Facebook historical data of over a thousand news outlets, encompassing approximately 57 million posts in four European languages from 2008 to the end of 2022. We discover universal growth dynamics according to which news virality is independent of the traditional size or engagement with the outlet. Moreover, our analysis reveals a significant long-term impact of news source reliability on engagement growth, with engagement induced by unreliable sources decreasing over time. We conclude the paper by presenting a statistical model replicating the observed growth dynamics.

Figures (12)

• Figure 1: (A-C) p-values of Mann-Whitney U tests between classes of size for Followers and Engagement growth rate distributions. Panel titles indicate the metric being tested and the metric according to which we determine the size. Row and column headers represent the class size. Bold numbers represent p-values for which we reject the hypothesis that the growth distributions do not differ, with the alternative hypothesis that the smaller class grows at a higher rate. For readability, 0 represents p-values smaller than 0.0001.
• Figure 2: Comparison of observed and theoretical growth rate distributions for Engagement and Followers. Red lines denote theoretical densities obtained by fitting empirical ones, with labels D, W, M, and Q indicating Daily, Weekly, Monthly, and Quarterly timescales.
• Figure 3: Results of growth simulation with different starting sizes. Sub-plot headers indicate the Followers starting value and the related timescale. Solid lines represent the mean cumulative distribution function value of the iteration time, shades represent the corresponding standard error.
• Figure 4: A) Comparison of Engagement growth rate distributions of Questionable and Reliable pages for different timescales. B) Mean growths of Questionable and Reliable pages across increasing timescales.
• Figure 5: (A) Pages' creation across time. (B) Evolution of the number of posts and Total Interactions over time.