Revealing Social Networks in Cities
Invisible Cities reveals social networks in the urban environment. It displays geocoded activity from online services such as Twitter and Instagram in real-time and in aggregate. Real-time activity is represented as individual markers that appear whenever a Tweet or image is posted. Aggregate activity is reflected in the underlying terrain—the landscape warps as data is accrued, creating hills and valleys representing areas with high and low densities of data. Built to support the Leap Motion Controller, Invisible Cities allows users to navigate the three-dimensional data landscape through natural gestures.
Invisible Cities supports the Leap Motion Controller for navigation via natural gestures
Inspired by situationist theory, the objective was to represent a city defined not by the architecture, but by the experience, the moment. This idea is expressed through narrative pathways connecting individual data points and based on themes emerging from the information. These pathways create dense meta-networks, blanketing the terrain and connecting disparate areas of the city. Invisible Cities was a collaboration with programmer and media artist, Liangjie Xia.
Invisible Cities spans multiple locations, from New York and San Francisco to Seattle and Tokyo. In each case, the visualization represents the unique characteristics of the selected city—while New York clearly shows a concentration of activity in Manhattan, social activity in Tokyo reflects its multiple city centers. Through its immersive, three-dimensional information landscape, Invisible Cities creates a parallel experience to the physical environment—one of intersections, discovery, and memory. The project has received widespread recognition. Read more about Invisible Cities at the Parsons Journal for Information Mapping.