The New York Times

Data Mapping Project





The New York Times Data Mapping Project is a visual representation of New York Times headlines for the month of January, 2006.

Each category of headline, such as "International," "NY/Region," or "Technology" is represented by a stuffed figure made from a different pattern of fabric. Figures are also differentiated by gender, as expressed by the names of headline article journalists. Where the gender was not obvious to me, such as "Robin," I researched that author to confirm his or her gender. Associated Press articles were eliminated from the data set, since they were not specific to the Times. This project assumed that any transgendered journalists, if there were any, expressed their gender identity through their names. This may or may not be an accurate assumption. Articles that I personally chose to read which were not main headlines were also eliminated from the data set. All data was culled from the New York Times online addition, generally around 7 am Pacific Time/10 am New York time. Stuffed figures representing female journalists are visually separated from those representing males.

The final data tally showed that about 22% of headline authors were female, and this tally would have been lower if there had not been a spike of articles written by women for the few days around the confirmation of Judge Samuel Alito to the Supreme Court. The final data set may also reveal something about what topics are most important to readers of the New York Times currently. For example, a comparison of the number of Technology headlines in the New York Times relative to the number in the San Jose Mercury News might potentially yield relevent information about audience demographics.

This piece is interactive in that I encourage people installing it to experiment and push for as many patterns for representing the data as possible. Here I show two simple possibilities for arrangement, a floor grid (with females on top) and a floor pie graph (with females on the left).








RAW DATA (use back button to return)