Preferential attachment models and their generalizations

Liudmila Ostroumova, Andrei Raigorodskii


Preferential attachment models were shown to be very effective in predicting such important properties of real-world networks as the power-law degree distribution, small diameter, etc. Many different models are based on the idea of preferential attachment (e.g., LCD, Buckley–Osthus, Holme–Kim, random Apollonian network, and many others). We will talk about preferential attachment models, their properties, and their generalizations, such as fitness and recency-based models. We will also discuss efficient algorithms for generating graphs in these models