Fabiana Zollo

TL;DR: A massive quantitative analysis of Facebook shows that information related to distinct narratives––conspiracy theories and scientific news––generates homogeneous and polarized communities having similar information consumption patterns, and derives a data-driven percolation model of rumor spreading that demonstrates that homogeneity and polarization are the main determinants for predicting cascades’ size.

TL;DR: This work addresses the diffusion of information about the COVID-19 with a massive data analysis on Twitter, Instagram, YouTube, Reddit and Gab, and identifies information spreading from questionable sources, finding different volumes of misinformation in each platform.

TL;DR: The findings show that communities’ emotional behavior is affected by the users’ involvement inside the echo chamber, and that, on average, more active users show a faster shift towards the negativity than less active ones.

TL;DR: The anatomy of the information space on Facebook is explored by characterizing on a global scale the news consumption patterns of 376 million users over a time span of 6 y, finding that users tend to focus on a limited set of pages, producing a sharp community structure among news outlets.

TL;DR: In this paper, a quantitative analysis of 2.6 million users with 298,018 Facebook posts over a time span of seven years and five months was performed to assess whether users' attitudes are polarized on the topic of vaccination on Facebook and how this polarization develops over time.