Alessandro Galeazzi

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: A massive analysis of the impact of lockdown measures introduced in response to the spread of novel coronavirus disease 2019 (COVID-19) on socioeconomic conditions of Italian citizens is presented and evidence of a segregation effect is found, since mobility contraction is stronger in municipalities in which inequality is higher and for those where individuals have lower income per capita.

TL;DR: In this article, a comparative analysis of more than 100 million pieces of content concerning several controversial topics (e.g., gun control, vaccination, abortion) from Gab, Facebook, Reddit, and Twitter was performed.

TL;DR: A framework to quantify the substantial impact of the mobility restrictions is provided and a percolation model mimicking mobility network disruption is introduced, finding that node persistence in the percolations process is significantly correlated with the economic and demographic characteristics of countries.

TL;DR: In this article, a massive comparative analysis on geolocalized data from 13 M Facebook users in France, Italy, and the UK was performed to assess the impact of those policies on human mobility.