Modeling spatial embedded social networks

Abstract

In this paper dierent models for social networks are reviewed. Two models which allow for spatial embedding social networks in physical space are chosen and applied. Both of the models are based on spatial interaction, where the probability for a tie between people decreases with increasing distance. The models are applied based on empirical data of egocentric social networks collected in Zurich, Switzerland. The analysis of the empirical data shows, that there is a strong exponential decrease of probability to maintain a social tie. Based on the empirical distribution of the social ties, the models are used to simulate spatially embedded networks to reproduce the tie length distribution in the empirical data.