Title: Generating online social networks based on socio-demographic attributes,
Abstract: Recent years have seen tremendous growth of many online social networks such
as Facebook, LinkedIn and MySpace. People connect to each other through these
networks forming large social communities providing researchers rich datasets
to understand, model and predict social interactions and behaviors. New
contacts in these networks can be formed due to an individual's demographic
attributes such as age group, gender, geographic location, or due to a
network's structural dynamics such as triadic closure and preferential
attachment, or a combination of both demographic and structural
characteristics.
A number of network generation models have been proposed in the last decade
to explain the structure, evolution and processes taking place in different
types of networks, and notably social networks. Network generation models
studied in the literature primarily consider structural properties, and in some
cases an individual's demographic profile in the formation of new social
contacts. These models do not present a mechanism to combine both structural
and demographic characteristics for the formation of new links. In this paper,
we propose a new network generation algorithm which incorporates both these
characteristics to model network formation. We use different publicly available
Facebook datasets as benchmarks to demonstrate the correctness of the proposed
network generation model. The proposed model is flexible and thus can generate
networks with varying demographic and structural properties.