# A sensible proof connecting the scale-free feature with the Zipf-law

## TL;DR

This paper establishes a rigorous theoretical link between the scale-free property of complex networks and the Zipf-law, providing a solid mathematical foundation for their connection and enabling the use of network analysis methods to study Zipf-law phenomena.

## Contribution

It presents a formal mathematical derivation connecting scale-free networks with Zipf-law through vertex rank, bridging empirical observations with theoretical proof.

## Key findings

- Derived an equivalent relation between scale-free features and Zipf-law.
- Eliminated the lack of theoretical foundation for Zipf-law.
- Validated the use of complex network analysis methods for Zipf-law studies.

## Abstract

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 $P_{cum}(k)\sim k^{1-\gamma}$ ($2<\gamma<3$). Meanwhile, the Zipf-law, which satisfies this $f_{r}\sim r^{-\alpha}$ ($\alpha$ 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