Geo-social networks like Facebook Places and Foursquare are revolutionising the use of location-based mobile services. Here, users can post information about their whereabouts, often pictures with geo-tagging of locations, and tagging of other people in the pictures, thus also geo-tagging these people. Like more general mobile analytics has now become an independent area ("mobilytics"), analytics of geo-social networks will also grow into the new area of "geosocialytics". This topic will seek to find the common building blocks of geosocialytics functionality, such as advanced data mining techniques, and provide efficient algorithms and techniques for the data management and computation of these. Examples include discovering cliques in terms of both interests and movement patterns and using the combined knowledge of the users' spatio-temporal and other behavior (e.g., what they eat or buy) to provide eco-friendly suggestions for alternative behavior, e.g., ridesharing or buying more sustainable products. An important aspect is the balancing of functionality and privacy: sometimes a computationally efficient approach will reveal too much sensitive information; instead more expensive, but privacy-preserving approaches are needed. Thus, the topic also contributes to Challenge 6.

Main Advisor at Aalborg Universitet (AAU)
Co-advisor at Université Libre de Bruxelles (ULB)