Maria Deijfen: Preferential attachment models and general branching processes

A much studied type of models for growing networks is based on so-called preferential attachment: vertices are successively added to the network and are attached to existing vertices with probability proportional to degree. This mechanism has been shown to lead to power law degree sequences, which is in agreement with empirical studies on many types of real networks. I shall describe how general branching processes can be used to derive results on the degree sequence in preferential attachment models and also in extensions of the model where vertices are not just added to the network but may also be removed.