Project Description
Networks of Audience Overlap in the Consumption of Digital News
How do people consume news online? Here, we propose a novel way to answer this question using the browsing behavior of web users and the networks they form while navigating news content. In these networks, two news outlets are connected if they share a fraction of their audiences. We propose two crucial improvements to the methodology employed in previous research: a statistical test to filter out non-significant overlap between sites; and a thresholding approach to identify the core of the audience network. We explain why our approach is better than previous approaches using two data sets: one tracks digital news consumption during the 2016 Brexit referendum in the UK and the other during the 2016 Presidential Election in the US. We show that our filtering technique produces a completely different ranking of top sites, uncovering structural properties in the audience network that would go unnoticed otherwise.
Citation: Mukerjee, S., Majó-Vázquez, S., & González-Bailón, S. (2018), Networks of Audience Overlap in the Consumption of Digital News. Journal of Communication, 68 (1), 26-50.
