Modelling Aging Characteristics in Citation Networks

Abstract

Growing network models with preferential attachment dependent on both age and degree are proposed to simulate certain features of citation network noted in \cite{red2}. In this directed network, a new node gets attached to an older node with the probability $\sim K(k)f(t)$ where the degree and age of the older node are $k$ and $t$ respectively. Several functional forms of $K(k)$ and $f(t)$ have been considered. The desirable features of the citation network can be reproduced with $K(k)\sim k^{-\beta }$ and $f(t)\sim \exp (\alpha t)$ with $\beta =2.0$ and $\alpha =-0.2$ and with simple modifications in the growth scheme.

6 pages, 6 figures

References in corpus (6)

• Statistical mechanics of complex networks
• Citation Statistics from 110 Years of Physical Review
• The effect of aging on network structure
• Life, Death and Preferential Attachment
• Accelerated growth in outgoing links in evolving networks: deterministic vs. stochastic picture
• Directed Accelerated Growth: Application in Citation Network

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• The dynamics of power laws: Fitness and aging in preferential attachment trees
• Scientometric engineering: Exploring citation dynamics via arXiv eprints
• Modeling nonuniversal citation distributions: the role of scientific journals
• Modeling citation networks based on vigorousness and dormancy
• Fractional stochastic model of citation dynamics with memory and volatility
• On the Predictability of Utilizing Rank Percentile to Evaluate Scientific Impact