How does social media content diffuse societies? Building a predictive model based on public metrics of Facebook content
The aim of the research was to explore how Facebook’s public metrics can be used to predict content’s potential for virality and spread in society.
To better understand the actual spread of information from Facebook, we mapped 10 viral posts on Facebook and then conducted an street survey (n=631) in Estonia, asking respondents if they had seen the content of these posts to measure what the actuarial reach of the posts was in society. Based on this data we we conducted regression analysis to determine the relationships between publicly available Facebook metrics and the post diffusion in society. Finally, we built a social media diffusion model that can predict reach of Facebook posts based on the public metrics.
The study shows that comments are the strongest factor in predicting the reach of posts and that actions by followers are not as influential as actions by people outside the content owner’s network.
Diana Poudel, University of Tartu