  We demonstrate the SciLens News Platform, a novel system for evaluating the
quality of news articles. The SciLens News Platform automatically collects
contextual information about news articles in real-time and provides quality
indicators about their validity and trustworthiness. These quality indicators
derive from i) social media discussions regarding news articles, showcasing the
reach and stance towards these articles, and ii) their content and their
referenced sources, showcasing the journalistic foundations of these articles.
Furthermore, the platform enables domain-experts to review articles and rate
the quality of news sources. This augmented view of news articles, which
combines automatically extracted indicators and domain-expert reviews, has
provably helped the platform users to have a better consensus about the quality
of the underlying articles. The platform is built in a distributed and robust
fashion and runs operationally handling daily thousands of news articles. We
evaluate the SciLens News Platform on the emerging topic of COVID-19 where we
highlight the discrepancies between low and high-quality news outlets based on
three axes, namely their newsroom activity, evidence seeking and social
engagement. A live demonstration of the platform can be found here:
http://scilens.epfl.ch.
