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Many of the essential features of the evolution of scientific research are imprinted in the structure of citation networks. Connections in these networks imply information about the transfer of knowledge among papers, or in other words, edges describe the impact of papers on other publications. This inherent meaning of the edges infers that citation networks can exhibit hierarchical features, that is typical of networks based on decision-making. In this paper, we investigate the hierarchical structure of citation networks consisting of papers in the same field. We find that the majority of the networks follow a universal trend towards a highly hierarchical state, and i) the various fields display differences only concerning their phase in life (distance from the birth of a field) or ii) the characteristic time according to which they are approaching the stationary state. We also show by a simple argument that the alterations in the behavior are related to and can be understood by the degree of specialization corresponding to the fields. Our results suggest that during the accumulation of knowledge in a given field, some papers are gradually becoming relatively more influential than most of the other papers.
Scientific journals are the repositories of the gradually accumulating knowledge of mankind about the world surrounding us. Just as our knowledge is organised into classes ranging from major disciplines, subjects and fields to increasingly specific t
Universality or near-universality of citation distributions was found empirically a decade ago but its theoretical justification has been lacking so far. Here, we systematically study citation distributions for different disciplines in order to chara
We analyse the large-scale structure of the journal citation network built from information contained in the Thomson-Reuters Journal Citation Reports. To this end, we take advantage of the network science paraphernalia and explore network properties
We introduce the concept of control centrality to quantify the ability of a single node to control a directed weighted network. We calculate the distribution of control centrality for several real networks and find that it is mainly determined by the
We present a simple generalization of Hirschs h-index, Z = sqrt{h^{2}+C}/sqrt{5}, where C is the total number of citations. Z is aimed at correcting the potentially excessive penalty made by h on a scientists highly cited papers, because for the majo