Research of ranking in temporal networks

The paper is devoted to the study of ranking in time-dependent networks. The paper provides an overview of the types and classes of networks, as well as the main centrality metrics, ranking approaches, and ranking algorithms. Within the framework of Bianconi-Barabasi networks, the correlation of the intrinsic fitness of nodes, which affects the evolution of the network, and the ranking results was studied. The paper draws conclusions regarding the interchangeability of some centralities and the expediency of using specific centralities and ranking approaches. The developed software can be used to expand and deepen ranking research in complex networks.