The preferential attachment model is designed for generating random networks in which the degree sequence follows a power-law distribution. We begin by examining the basic model and derive the properties of the resulting degree sequence. This is followed by a discussion of citation networks between scientific articles. Finally, we consider several possible extensions of the basic model and highlight their specific features. We primarly focus on the resulting degree distribution of the nodes.
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