On the impact of network size and average degree on the robustness of centrality measures

Research output: Journal contributionsJournal articlesResearchpeer-review

Authors

Measurement errors are omnipresent in network data. Most studies observe an erroneous network instead of the desired error-free network. It is well known that such errors can have a severe impact on network metrics, especially on centrality measures: a central node in the observed network might be less central in the underlying, error-free network. The robustness is a common concept to measure these effects. Studies have shown that the robustness primarily depends on the centrality measure, the type of error (e.g., missing edges or missing nodes), and the network topology (e.g., tree-like, core-periphery). Previous findings regarding the influence of network size on the robustness are, however, inconclusive. We present empirical evidence and analytical arguments indicating that there exist arbitrary large robust and non-robust networks and that the average degree is well suited to explain the robustness. We demonstrate that networks with a higher average degree are often more robust. For the degree centrality and ErdÅ's-Rényi (ER) graphs, we present explicit formulas for the computation of the robustness, mainly based on the joint distribution of node degrees and degree changes which allow us to analyze the robustness for ER graphs with a constant average degree or increasing average degree.

Original languageEnglish
JournalNetwork Science
Volume9
Issue numberS1
Pages (from-to)S61-S82
Number of pages22
ISSN2050-1242
DOIs
Publication statusPublished - 20.10.2021
EventInternational Conference on Complex Networks and their Applications - 2019: Complex Networks - Calouste Gulbenkian Foundation, Lisbon, Portugal
Duration: 10.12.201912.12.2019
Conference number: 8
https://www.complexnetworks.org/index

Bibliographical note

Special Issue S1: Complex Networks 2019. © The Author(s), 2020. Published by Cambridge University Press

Documents

DOI

Recently viewed

Researchers

  1. Matthias Gaßmann

Publications

  1. Regulating Nimbus and Focus
  2. Heterogenitätssensible Hochschullehre
  3. The implications of knowledge hiding at work for recovery after work: A diary study
  4. Divert when it does not hurt
  5. Conditions of One-Way and Two-Way Approaches in Strategic Start-Up Communication
  6. Experimental investigation of crack propagation mechanism in refill friction stir spot joints of AA6082-T6
  7. The Structure and Behavioural Effects of Revealed Social Identity Preferences
  8. Insight into layer formation during friction surfacing
  9. The importance of understanding the multiple dimensions of power in stakeholder participation for effective biodiversity conservation
  10. Influence of measurement errors on networks
  11. Introduction to the basics of life cycle sustainability assessment focusing on the UNEP/SETAC Life Cycle Initiative LCSA framework
  12. No-Code Platforms in Startups: Explaining Decisions for Adoption and Abandonment
  13. Later Life Workplace Index: Validation of an English Version
  14. Fast response of groundwater to heavy rainfall
  15. Control of Permanent Magnet Synchronous Motors for Track Applications
  16. Fatigue crack propagation in AA5083 structures additively manufactured via multi-layer friction surfacing
  17. Kultur als Materialität oder Material – Diskurstheorie oder Diskursanalyse?
  18. Schulleistung in Diskussion
  19. Recognizing Guarantees and Assurances of Non-Repetition
  20. Die Bedeutung der Zeit
  21. University-linked programmes for sustainable entrepreneurship and regional development
  22. Mindsets and reflection in teacher education for inclusive language classrooms
  23. The influence of balanced and imbalanced resource supply on biodiversity-functioning relationship across ecosystems
  24. Nutzen – Nutzung - Nutzer_innen
  25. Uncertainty, Pluralism, and the Knowledge-based Theory of the Firm
  26. Lexical markers of common grounds
  27. Vorstellungen über null und Null