The aggregation of editorial content with other media resources contributes to the enhancement of media production. This project combines several deep learning techniques to reduce the risk of generating false aggregations, and translates the resulting credibility boost into added value that can be perceived by users.
Trust Over Time
Summary
Keywords :
artificial intelligence, deep learning, media, trust, interaction design, user perception
artificial intelligence, deep learning, media, trust, interaction design, user perception
| Duration | 12 months |
| People involved | Principal investigators Nicolas Henchoz (EPFL) Prof. Daniel Gatica-Perez (Idiap Research Institute)
Researchers Delphine Ribes (EPFL) Lara Défayes (EPFL) Hélène Portier (EPFL) Lazar Stojkovic (EPFL) Thanh-Trung Phan (Idiap Research Institute)
Media partners Vincent Seriot (RTS) Pietro Rezzonico (RTS) |
| Academic institutions | EPFL+ECAL Lab (EPFL) Social Computing Group (Idiap Research Institute) |
| Media partners | RTS – Radio Télévision Suisse (SRG) – Data and Archives (D+A) |
| Status | This project started in October 2019 and is ongoing |