The analysis of symmetry is a main principle in natural sciences, especially physics. For network sciences, for example, in social sciences, computer science and data science, only a few small-scale studies of the symmetry of complex real-world graphs exist. Graph symmetry is a topic rooted in mathematics and is not yet well-received and applied in practice. This article underlines the importance of analyzing symmetry by showing the existence of symmetry in real-world graphs. An analysis of over 1500 graph datasets from the meta-repository networkrepository.com is carried out and a normalized version of the “network redundancy” measure is presented. It quantifies graph symmetry in terms of the number of orbits of the symmetry group from zero (no symmetries) to one (completely symmetric), and improves the recognition of asymmetric graphs. Over 70% of the analyzed graphs contain symmetries (i.e., graph automorphisms), independent of size and modularity. Therefore, we conclude that real-world graphs are likely to contain symmetries. This contribution is the first larger-scale study of symmetry in graphs and it shows the necessity of ha ... mehr

Zugehörige Institution(en) am KIT |
Institut für Informationswirtschaft und Marketing (IISM) |

Publikationstyp |
Zeitschriftenaufsatz |

Jahr |
2018 |

Sprache |
Englisch |

Identifikator |
ISSN: 2073-8994 URN: urn:nbn:de:swb:90-801519 KITopen ID: 1000080151 |

Erschienen in |
Symmetry |

Band |
10 |

Heft |
1 |

Seiten |
29 |

Bemerkung zur Veröffentlichung |
Gefördert durch den KIT-Publikationsfonds |

Schlagworte |
graph symmetry; graph automorphism groups; symmetry analysis; real-world networks |

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