xLiMe proposes to extract knowledge from different media channels and languages and relate it to cross-lingual, cross-media knowledge bases. By doing this in near real-time we will provide a continuously updated and comprehensive view on knowledge diffusion across media, e.g., from European communities like Catalonia to worldwide content in English. By combining speech recognition, natural language processing, machine learning and semantic technologies we will advance key open research problems, by:

1. extracting machine-readable knowledge (entities, sentiment, events and opinions) from multilingual, multimedia and social media content and integrate it with cross-lingual, cross-media knowledge bases,
2. searching this knowledge with structured and unstructured queries in near real-time,
3. monitoring its provenance, consumption and diffusion and
4. analysing the interdependency between media exposure and behavioural patterns