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Exploring the raison d'etre behind metric selection in network analysis: a systematic review
D Morrison1, M Bedinger1, L Beevers1
1School of Energy, Geosciences, Infrastructure and Society, Heriot-Watt University, William Arrol Building, Room W.A. 3.36/3.37, 2 Third Gait, Currie, Edinburgh, EH14 4AS UK.
Applied Network Science
|July 20, 2022
Summary
Network analysis uses graph metrics to understand complex systems. This review clarifies metric selection for robust analysis, recommending explicit rationale and holistic metric choices for better insights.
Area of Science:
- Complex Systems Science
- Graph Theory
- Urban Studies
Background:
- Network analysis is crucial for understanding entity interactions and system structures.
- The rapid growth of network analysis has led to a proliferation of metrics, causing challenges in selection.
- Polysemic metrics in network analysis require careful consideration for accurate interpretation.
Purpose of the Study:
- To provide clarity on the rationale behind selecting network analysis metrics.
- To suggest a structured approach for applied network analysis.
- To guide researchers in choosing appropriate metrics for their studies.
Main Methods:
- Structured literature review of network analysis metrics.
- Exploratory analysis of metric selection criteria.
- Discussion on the relationship between mathematical metrics and conceptual themes.
Main Results:
- Identified challenges in metric selection due to metric diversity and polysemy.
- Emphasized the need for explicit reporting of the rationale behind metric choice.
- Highlighted the importance of exploratory metric analysis to identify key and redundant metrics.
Conclusions:
- Future studies must clearly state the justification for chosen network analysis metrics.
- Selecting an optimal number of metrics is crucial for a holistic understanding of network properties.
- Applied network analysis benefits from a systematic approach to metric selection and interpretation.
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