2019/04/17 by Fei Ma, Ma, Fei
Biochemistry, Genetics and Molecular Biology · Physics and Astronomy · #Bioinformatics and Genomic Networks #Complex Network Analysis Techniques #FOS: Physical sciences #Opinion Dynamics and Social Influence #Physics and Society (physics.soc-ph)
paper · pdf · doi:10.48550/arxiv.1904.08065
openalex publication_date 2019/04/17 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Most of various large-size complex systems in nature and society can be well described as complex networks (graphs) to better understand the evolutional mechanisms and dynamical functions behind themselves. Of some part follow scale-free behavior, that is, the ratio of the number of vertices with degree more than or equal to k and order of the whole network obeys the expression Pcum(k)∼ k1-γ (2<γ<3). Meanwhile, the Zipf-law, which satisfies this fr∼ r-α (α close to unity), is also prevalent in many complex systems, such as word frequencies in text and city sizes. It can be easily noticed that the both above have same type of appearance, namely the known power-law. Compared to the scale-free feature proofed analytically by continuum theory, by far the latter in most cases still is thought of as an empirical principle in lots of science communities, particularly in social science. For this reason there is a need for either pointing out the inner connection between the two or distinguishing difference of one another. Here, for any arbitrary given scale-free network model of order N, we report an equivalent relation between scale-free feature and the Zipf-law based on the vertex rank. By rigorous mathematical derivations, we eliminate the gap, lack of theoretical fundament of the Zipf-law. Therefore one can be convinced that it is reasonable to adopt methods already used to study complex networks to do the Zipf-law