Titlebook: Citation Analysis and Dynamics of Citation Networks; Michael Golosovsky Book 2019 The Author(s), under exclusive license to Springer Natur

Nostalgia

Fabric

Comparison to Existing Models,f the empirical preferential attachment model. We show that the initial attractivity is determined by the width of the fitness distribution. We compare the preferential attachment and fitness models to our microscopic model of citation dynamics based on recursive search and show that our model contains both these phenomenological models.

爱哭

Complex Network of Scientific Papers,e explain this network approach and make special accent on the temporal aspect of citation network, namely, we focus on the growth of the number of papers, age distribution of references, and citation dynamics. We trace relation of the age distribution of references to citation dynamics and explore

咒语

Stochastic Modeling of References and Citations,ive search algorithm. We put this algorithm at the core of the quantitative model accounting for the age composition of the reference lists of papers. The model contains two empirical functions: the aging function and the obsolescence function, and one empirical parameter—paper’s fitness. At the nex

extinguish

大约冬季

irreducible

Power-Law Citation Distributions are Not Scale-Free, follow the power-law dependence, we find that they are nonstationary and the exponent of the power-law fit decreases with time and does not come to saturation. We attribute the nonstationarity of citation distributions to different longevity of the low-cited and highly-cited papers. By measuring ci

一个姐姐

Comparison to Existing Models,itions these models are equivalent. In order to find the microscopic foundations of the preferential attachment mechanism, we analyze theoretically and experimentally several citation networks and demonstrate that, for a broad fitness distribution, this mechanism reduces to the fitness model. The fi

审问

Citation Analysis and Dynamics of Citation Networks

indifferent