Seminar Details
2019-03-05 (14:00) : Diffusion in complex systems: random walks, fast ions and fake news
At Euler building (room A.002)
Organized by Mathematical Engineering
Speaker :
Bovet, Alexandre
Abstract :
After a quick overview of my past work on the anomalous diffusion of fast ions in turbulent plasmas I will present
my recent work on the investigation of diffusion of news in Twitter.
To understand the role of fake news in Twitter during the 2016 US election, we combined machine learning,
network science, statistical physics and causality analysis to not only measure the importance of fake news
compared to traditional news in Twitter but also understand their influence and the mechanisms of their diffusion.
Using a dataset of more than 170 million tweets covering the five months preceding election day and concerning
the two main candidates of the 2016 US presidential election, we find that 25% of the tweets linking to a news spread
either fake or extremely biased news. We analyzed the networks of information flow and found the most important
news spreaders by using the theory of optimal percolation and used a multivariate causal network reconstruction to
uncover how fake news influenced the presidential election.
I will end with the presentation of my current work and my future research plan about random walks to investigate
spatio-temporal structures in temporal networks.