# Quantitative Graph Theory: A new branch of graph theory and in network science

arXiv: https://arxiv.org/abs/1710.05660 · HTML: https://mlsanity.com/paper/1710.05660/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 12 Oct 2017.

## Built on by (most cited first, 1 of 1)

- [Measuring Structure in Graph Benchmark Datasets Using Graph Invariants](https://mlsanity.com/paper/2605.06462/) (2026)

## Abstract (arXiv)

In this paper, we describe sc quantitative graph theory and argue it is a new graph-theoretical branch in network science, however, with significant different features compared to classical graph theory. The main goal of quantitative graph theory is the structural quantification of information contained in complex networks by employing a it measurement approach based on numerical invariants and comparisons. Furthermore, the methods as well as the networks do not need to be deterministic but can be statistic. As such this complements the field of classical graph theory, which is descriptive and deterministic in nature. We provide examples of how quantitative graph theory can be used for novel applications in the context of the overarching concept network science.