Technology & Science·Audio

Social mapping software turns neighbourhoods into 'Livehoods'

You might have no doubt about what neighbourhood you live in, but can you pinpoint your livehood? If you're in Montreal, you can now, thanks to a new mapping software that redraws traditional city boundaries using data gleaned from social media applications such as Twitter and Foursquare.
A map of 'Livehoods' in Montreal. Groups of same-coloured dots indicate the same sets of people have checked into those locations on Foursquare, meaning they have a shared social but not necessarily geographic affinity. (Livehoods.org)

You might think you know what neighbourhood you live in, but can you pinpoint your Livehood?

If you're in Montreal, you can now, thanks to a new mapping software that redraws traditional city boundaries using data gleaned from social media services such as Twitter and Foursquare, a mapping application for smartphones that allows users to alert others when they are at a certain store, restaurant or other place of business.

Everybody knows that neighbourhoods are defined as much by the people who live in them as by their official geographic boundaries, but sometimes the two don't always correspond.

"The city is always changing, and neighbourhoods evolve much more rapidly than the boundaries that delineate them, and often, these fixed boundaries — they do not necessarily reflect the nature of the cultural perceptions people have of the city," Justin Cranshaw, the computer scientist who with some fellow PhD students and professors at Carnegie Mellon University created Livehoods, told Nora Young in an interview on CBC's Spark radio program.  

"We wanted to come up with a computational approach to discovering these natural neighbourhoods."

The software groups locations in a city into agglomerations called Livehoods based on whether a lot of the same people have checked into the same places on Foursquare.

"If many of the same people who check into a café also check into the grocery store around the corner, we'll identify a strong relationship between the café and the grocery," Cranshaw told Spark. "On the other hand, if the set of people that check into the cafe don't check into the movie theatre across the street, then we identify a weaker relationship."

To date, Cranshaw and his colleagues have used their system to create Livehood maps of New York, San Francisco Pittsburgh and, most recently, Montreal.

Listen to Nora Young's interview with Cranshaw here, or tune in to Radio 1 at 1:05 ET on June 3 or to Sirius Satellite Radio 159 at 6:00 ET on June 2.

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