Social network Architectures of Disinformation (#sad)


Social networks have become by far the most important place online to discuss and exchange information, but they also tend to polarize discussions and isolate users in their own cultural or ideological bubbles. This project aims to develop new methods to analyze the structure and mechanisms of influence within these communities, and to estimate the overall activity of social networks from only a partial view of them. Based on these methods, a tool will be developed to enable journalists to monitor the propagation of controversies and misinformation on platforms such as Twitter, YouTube and Reddit.

Presentation of the project results at the IMI Annual Event (24.09.2020)

Watch on YouTube

Keywords :
social networks, graph signal processing, network analysis, dynamic activity over networks, fake news

12 months

People involved

Principal investigator

Prof. Pierre Vandergheynst (EPFL)



Benjamin Ricaud (EPFL)

Nicolas Aspert (EPFL)

Andreas Loukas (EPFL)

Volodymyr Miz (EPFL)

Prof. Nathalie Pignard-Cheynel (UniNE)

Vincent Carlino (UniNE)

Lucie Loubère (Toulouse III University)



Amin Mekacher (EPFL)

Fanny Scuderi (UniNE)


Media partners

Magali Philip (RTS)

Tybalt Félix (RTS)

Academic institutions

Signal Processing Laboratory 2 – LTS2 (EPFL)

Academy of Journalism and Media – AJM (UniNE)

Media partner

RTS – Radio Télévision Suisse (SRG) – RTSinfo


This project started in September 2019 and has been completed

Related call for projects

Helping media fight misinformation and restore the public’s trust