Misinformation on social media: are fake news digital viruses?
Introduction
Fake-news spreading on social media can be seen as a digital virus spreading on the network of accounts: a user who shares a fake news item exposes their followers, who may share it further. Unlike in classical epidemic models, where the infection rate is constant in time, the spreading of fake news is bursty: the infection rate is very high as soon as the fake news is posted and decreases afterwards, which makes the process non-Markovian. Understanding the laws behind this spreading is essential to design strategies to detect and contain misinformation.
Project
The objective of this project is to quantify, from existing datasets of information propagation, the dynamical laws and parameters that describe the spread of misinformation. You will process and analyse real spreading data, fit epidemic models with time-dependent infection rates, and compare the spreading of fake and true news.
Skills: data processing, analysis and modelling
Contact
Federico Ravazzolo,
References
S. Vosoughi, D. Roy & S. Aral, "The spread of true and false news online", Science 359, 1146–1151 (2018).
K. Shu et al., "FakeNewsNet: A data repository with news content, social context, and spatiotemporal information for studying fake news on social media", Big Data 8(3), 171–188 (2020).