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 implies that citation networks can exhibit hierarchical features that are 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 the various fields display differences only concerning (i)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 other papers.
|Journal||Journal of Statistical Mechanics: Theory and Experiment|
|Publication status||Published - May 2014|
ASJC Scopus subject areas
- Statistical and Nonlinear Physics
- Statistics and Probability
- Statistics, Probability and Uncertainty