In recent years automatic text recognition has gotten more accurate and large amounts of old newspaper articles have been digitised. This allows humanities researchers to use a broader range of computer-aided methods for exploration and sensemaking of this data. Researchers are investigating connections between different publication sources, such as propagation patterns of news. However, they are limited in their pursuit of insight by a lack of tools for exploration and management of such data. Especially for huge datasets, visualisation can greatly improve the search for patterns and anomalies, and help reduce the cognitive load on the user. We create an approach that provides an overview visualisation and exploration capabilities for a collection of newspaper articles, their release dates and publication locations. The approach provides cues on the geographical locations of the visualised data without having to rely on a world map as its core component, freeing up space for other parts of the visualisation. We use brushing and linking throughout the visualisation to provide more context to the user. The dataset can be drilled down into, allowing further exploration, such as filtering by date, location or used words. In an expert review with a researcher in American studies, we evaluate the usefulness of the approach and collect feedback. The general response is that the approach can be useful for researchers. Finally, we provide a discussion and an outlook on future improvements.