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

Research output: Contribution to journalArticleScientificpeer-review


Original languageEnglish
Pages (from-to)575-580
Number of pages6
JournalInformation Sciences
Publication statusPublished - 1 Dec 2017
Publication typeA1 Journal article-refereed


In this paper, we describe some highlights of the new branch QUANTITATIVE GRAPH THEORY and explain its 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 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.


  • Data Science, Graphs, Networks, Quantitative Graph Theory, Statistics

Publication forum classification

Field of science, Statistics Finland