Organisations and individuals that need to monitor what the media say about certain issues face an extreme information overload, especially if they are interested in the news written in more than one language. News aggregators sometimes pre-filter potentially user-relevant articles or automatically group related articles into clusters. However, the enormous amount of available online information calls for further automatic information processing to enable users to sieve through even larger amounts of textual data in less time and to navigate and explore the document collections efficiently. NewsExplorer is a freely available news analysis system that offers such functionality in 19 languages. NewsExplorer integrates various text analysis applications including clustering, multi-label document classification, named entity recognition, name variant matching across languages and writing systems, topic detection and tracking, and more. The purpose of this presentation is to present this news exploration and analysis system and to especially address the multilinguality issue and the cross-lingual functionality of the application. References to prior art will be made, where appropriate.