Who are we?

Founded in 2005, The Friendly Cities Lab is an active research group within the Departments of Interactive Computing and Urban Planning at Georgia Tech. FCL is a Smart Cities initiative that studies interpersonal relationships in geographic space. We create a new measure of geographical nearness called ‘social distance’ to measure how ‘close’ places based on their connections instead of how close they are on a map. We use innovative data sets ranging from chocolate, online dating, phone calls, and photos of living rooms to learn just a little bit more about the planet and its people.

Our Projects

Our research themes include Social Flow Theory, Social Distance, Spatial Networks, and love, friendship, family, and relationships in the city. Check some of our projects out!

Exploring Institution-Driven Mobility
Findings: Certain colleges like West Virginia and Providence have much less ‘pull power’ to attract far-away athletes than schools like Stanford
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Visualizing Commuting in Singapore
Findings: Singapore has good public transportation and other mobility options making it easy to get around the city. Method: a visualization
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Development, Information and Social Connectivity in Côte d’Ivoire
Findings: Despite a devastating N-S Civil War, phone calls still connect N-S cities, moreso than E-W cities. Coastal cities host
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Relevant Literature for Examining Social Networks in Geographic Space
Findings: Some great publications show us that social interaction studies would be better if they included GIS. For example, an otherwise
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Support Vector Machine for Spatial Variation
Findings: Given it’s ability here to find geographic variances in students admitted to a university, the Support Vector Machine is
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Discovering Spatial Patterns in Origin-Destination Mobility Data
Findings: It’s hard to create a chart showing where a million people were picked up and dropped off. We can use
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Neighborhood Differentiation and Travel Patterns in Singapore
Findings: Understanding how people travel through Singapore and how successful the existing travel options are in connecting those people to
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Weighted Radial Variation for Node Feature Classification
Findings: A technique called Weighted Radial Variation makes it easier to visualize migration connections created from a node-edge matrix. Method: Extracting stars
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Predicting Migration Dynamics with Conditional and Posterior Probabilities
Findings: People’s social ties, not just cost and distance, play a role in deciding where people migrate. Method: A Bayesian place-pair
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Redrawing the Map of Great Britain from a Network of Human Interactions
Findings: The boundaries of regional governments correspond quite well with how people communicate via phone in the UK. Scotland is the
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Our Lab Location