Obiettivo In the past decade, social media have become one of the main sources of news for people around the world. Yet, it comes with the danger of exposure to intentionally false information. The extensive spread of fake news has recently become a centerpiece of controversy following the highly debated elections of President Donald Trump and the Brexit vote. It is alleged that the outcome of these votes resulted from the public opinion manipulation by a massive injection of fake news, possibly sponsored by hostile foreign governments, constituting perhaps one of the most serious and unprecedented threats to the modern democracies. The ambition of GoodNews is to build the technological capability for algorithmic fake news detection in social media using a novel paradigm. Instead of following the traditional approach of analyzing the news content, we will analyze the news spreading patterns in social networks. The algorithmic core of GoodNews is based on a novel class of geometric deep learning algorithms developed in the ERC project LEMAN (Learning on Manifolds and Graphs). Our research group was among the first in the world to propose, implement, and patent generalizations of popular convolutional neural network architectures to graph-structured data such as social networks, allowing to do deep learning on graphs. The ability to learn fake news spread patterns on social networks will provide the needed breakthrough in the task of automated fake news detection. GoodNews will convert the geometric deep learning technology into a commercial application of fake news detection in social media. The focus of the project will be three-fold: developing a demo system for fake news detection with real data from social media; verifying and solidifying our IP portfolio and its licensing terms; analyzing the market and coming up with a financeable business plan. We target establishing a company at the end of the project and attracting investment to develop a commercial-grade product. Campo scientifico natural sciencescomputer and information sciencesartificial intelligencemachine learningdeep learningnatural sciencescomputer and information sciencesartificial intelligencecomputational intelligence Parole chiave fake news detection social media social network analysis geometric deep learning deep learning on graphs Programma(i) H2020-EU.1.1. - EXCELLENT SCIENCE - European Research Council (ERC) Main Programme Argomento(i) ERC-2018-PoC - ERC Proof of Concept Grant Invito a presentare proposte ERC-2018-PoC Vedi altri progetti per questo bando Meccanismo di finanziamento ERC-POC - Proof of Concept Grant Istituzione ospitante UNIVERSITA DELLA SVIZZERA ITALIANA Contribution nette de l'UE € 150 000,00 Indirizzo VIA GIUSEPPE BUFFI 13 6900 Lugano Svizzera Mostra sulla mappa Regione Schweiz/Suisse/Svizzera Ticino Ticino Tipo di attività Higher or Secondary Education Establishments Collegamenti Contatta l’organizzazione Opens in new window Sito web Opens in new window Partecipazione a programmi di R&I dell'UE Opens in new window Rete di collaborazione HORIZON Opens in new window Costo totale € 150 000,00 Beneficiari (1) Classifica in ordine alfabetico Classifica per Contributo netto dell'UE Espandi tutto Riduci tutto UNIVERSITA DELLA SVIZZERA ITALIANA Svizzera Contribution nette de l'UE € 150 000,00 Indirizzo VIA GIUSEPPE BUFFI 13 6900 Lugano Mostra sulla mappa Regione Schweiz/Suisse/Svizzera Ticino Ticino Tipo di attività Higher or Secondary Education Establishments Collegamenti Contatta l’organizzazione Opens in new window Sito web Opens in new window Partecipazione a programmi di R&I dell'UE Opens in new window Rete di collaborazione HORIZON Opens in new window Costo totale € 150 000,00