This paper presents a stochastic model for spatially embedded social networks based on the ideas of spatial interaction models. Analysing empirical data, we find that the probability to accept a social contact at a certain distance follows a power law with exponent -1.6. With a simulation where the spatial distribution of vertices is defined by a synthetic population of Switzerland, we can reproduce the edge length distribution observed in the empirical data as well as some other typical properties of social networks.