> New York Times Topic Map

An internal data visualization project combining aggregated traffic data from NYTimes.com with article metadata. Topic metadata (comprised of New York Times taxonomic classifiers) is parsed from articles read by users. These topics are then mapped to the users’ geographic locations, thereby visually illustrating the relative interest in topics for different locations within the United States. The visualization cycles between a topic view, which shows interest in a particular topic across all states, and a state view, which shows the most-read topics for a particular state. The visualization is installed on screens in the R&D lab, and is intended to be an ambient, glanceable visualization that allows insights into how our readers consume New York Times content.

Role: Concept, design, programming

Year: 2009