Geo-Social Simulation

Urban life: a model of people and places, Andreas Züfle, Carola Wenk, Dieter Pfoser, Andrew Crooks, Joon-Seok Kim, Hamdi Kavak, Umar Manzoor, and Hyunjee Jin Abstract We introduce the Urban Life agent-based simulation used by the Ground Truth program to capture the innate needs of a human-like population and explore how such needs shape social constructs such as friendship and wealth. Urban Life is a spatially explicit model to explore how urban form impacts agents’ daily patterns of life. By meeting up at places agents form social networks, which in turn affect the places the agents visit. In our model, location and co-location affect all levels of decision making as agents prefer to visit nearby places. Co-location is necessary (but not sufficient) to connect agents in the social network. The Urban Life model was used in the Ground Truth program as a virtual world testbed to produce data in a setting in which the underlying ground truth was explicitly known. Data was provided

Location-Based Social Network Data Generation Based on Patterns of Life Joon-Seok Kim, Hyunjee Jin, Hamdi Kavak, Ovi Chris Rouly, Andrew Crooks, Dieter Pfoser, Carola Wenk, Andreas Züfle Abstract Location-based social networks (LBSNs) have been studied extensively in recent years. However, utilizing real-world LBSN data sets yields several weaknesses: sparse and small data sets, privacy concerns, and a lack of authoritative ground-truth. To overcome these weaknesses, we leverage a large-scale LBSN simulation to create a framework to simulate human behavior and to create synthetic but realistic LBSN data based on human patterns of life. Such data not only captures the location of users over time but also their interactions via social networks. Patterns of life are simulated by giving agents (i.e., people) an array of "needs" that they aim to satisfy, e.g., agents go home when they are tired, to restaurants when they are hungry, to work to cover their financial needs, a