Curator: Jer Thorp
date: March 3, 2014
Categories: Information Design
Tags: dataviz, digital humanities, exploration, interface design, selfies
Screenshot from

While the entertainment world is buzzing about last night’s multi-celebrity selfie, data viz fans have been drooling over Selfiecity, an exploratory tool for examining selfie behavior across five global cities.

What’s in a selfie?

Or, more accurately, what’s in 3200 selfies? 

Selficity, a new tool from new media theorist Lev Manovich and data visualization expert Moritz Stefaner, offers an exploratory window into the world of the digital self portrait. The system uses a database of 3200 selfies, each identified from a large pool of Instagram photos by workers on Amazon’s Mechanical Turk. These images come from five cities across the world (Bangkok, Berlin, New York, Moscow & Sao Paolo), and visitors can use an intuitive interface to see how patterns emerge from geography, gender and age.

Do selfie-ers in Brazil smile more than Instagram users in Moscow? (Yes.)

Do women tend to tilt their heads more than men when they’re taking a selfie? (Yes.)

These questions might seem frivolous, and indeed, with such a small pool of photographs, you’d be right to question the accuracy of the answers. Still, Selfiecity offers a peek into the opportunities that big data and creative interface design can provide for the digital humanities. It also provides a working model for what an exploratory data tool can be. While most visualizations offer a limited number of conclusions to be drawn from the data, Selfiecity largely leaves the answers to the users of the tool. 

Which means there is ample room for selfie-exploration.

Head over to to explore, and then read this post by Moritz Stefaner about how the project was conceived and built.
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