Social network Architectures of Disinformation (#sad)

Summary

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.

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

12 months

People involved

Principal investigator

Prof. Pierre Vandergheynst (EPFL)

 

Researchers

Benjamin Ricaud (EPFL)

Nicolas Aspert (EPFL)

Andreas Loukas (EPFL)

Volodymyr Miz (EPFL)

Amin Mekacher (EPFL)

Prof. Nathalie Pignard-Cheynel (UniNE)

Vincent Carlino (UniNE)

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 partners

RTS – Radio Télévision Suisse (SRG) – RTSinfo

Status

This project started in September 2019 and is ongoing

Related call for projects

Helping media fight misinformation and restore the public’s trust