Happy Map

The Happy map by Alvin Chang, a data journalist and professor at The New School.

In 2017, more than 10,000 people tracked experiences that made them happy as part of a research project. The researchers gathered more than 100,000 happy moments.

Map methodology

The map is initially split up into 200,000 regions using a voronoi algorithm; it looks like a giraffe's fur. From there, the top-level category—the “continents”—are initially given a starting atom, based on the average agency and time scores. It is then allowed to take over atoms based on the countries, states, and cities (moments) that it needs to fit within its bounds. That conquering process determined what the map looks like. This ultimately means that the moments mostly follow the x- and y-axis of time and agency, like a scatterplot. But since two things can't occupy the same space, it's not a perfect scatterplot. The moments are then placed on the map with illustrations of people. The people were drawn on paper with an ink pen and fountain pen, then digitized so they could be used as icons.

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