Towards Data-Driven Generation of Visualizations for Automatically Generated News Articles

A feature news story is often accompanied by illustrations and visuals. These visualizations can be, e.g., timelines, line charts, pie charts, or images. In this article, we present a largely data-driven and domain-independent approach for generating visualizations to accompany automatically generated news articles. We demonstrate the feasibility of our approach by applying it to statistical data on crime in Finland. The practical implementation demonstrates how the automatically generated visualizations provide additional information and interactivity to the news articles. We further illustrate how the approach presented is easily transferable to different domains with structured numerical datasets.

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