Semantic Web Dog Food

Presented at: 19th International World Wide Web Conference (WWW2010)

by Cameron Marlow, Lars Backstrom, Eric Sun

Geography and social relationships are inextricably inter- twined; the people we interact with on a daily basis almost always live near us. As people spend more time online, data regarding these two dimensions – geography and so- cial relationships – are becoming increasingly precise, allow- ing us to build reliable models to describe their interaction. These models have important implications in the design of location-based services, security intrusion detection, and so- cial media supporting local communities. Using user-supplied address data and the network of asso- ciations between members of the Facebook social network, we can directly observe and measure the relationship be- tween geography and friendship. Using these measurements, we introduce an algorithm that predicts the location of an individual from a sparse set of located users with perfor- mance that exceeds IP-based geolocation. This algorithm is efficient and scalable, and could be run on hundreds of millions of users.

Keywords: Measuring, explaining properties of social networks

Resource URI on the dog food server: http://data.semanticweb.org/conference/www/2010/paper/main/993

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