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SAMS

· Data vs Fake News

A user-friendly research-based solution, simple tool to help check the facts.Use SAMS - Source, Author, Message, Spelling!

Team: Matthieu Delaloye, Camille Pellaton, Zhan Liu, Zarina Charlesworth, Maximiliano Jeanneret Medina, Shaban Shabani, Stéphane Bossel, Jérémy Orsat, Pierre Bossetti, Colm Kuonen, Laurin Weber, Alexandre Cotting, Ruanda Qamili

We found that the fake news regarding COVID-19 is spreading as fast as the virus.

We learned that real news can actually be counterintuitive, just one of the reasons why people believe fake news.

We identified a need for a user-friendly tool that could be used by children and adults alike to prevent the widespread dissemination of fake news.

We built a machine-learning based classification based on our collected data, including the fake news and the real news to help users to identify the fake news.

We designed a user-friendly tool that can increase the awareness of the population and help people become fact checkers on their own.

The biggest challenge in our project was at the stage of fake news data collection. Due to the recent apparition of COVID-19 we were unable to find an accessible database for the research and had to rely mostly on fake news spreading on the social media which we had to collect manually.