In this work, we introduce Social Minder, a Big Data platform for Social Media monitoring that allows massive extraction of textual information, and
stands on a modular and scalable architecture for efficient real-time and batch processing. This demo is oriented to present a use case that provides users with estimates of credibility for webpages linked in Social Media. Social Minder can serve multiple research and commercial purposes but we use it here for identifying COVID-19 related misinformation posted on Twitter.
Palabras clave: Big Data, Real Time, Web Streams, Credibility