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Generalizations of the clustering coefficient to weighted complex networks
Open accessAbstract
The recent high level of interest in weighted complex networks gives rise to a need to develop new measures and to generalize existing ones to take the weights of links into account. Here we focus on various generalizations of the clustering coefficient, which is one of the central characteristics in the complex network theory. We present a comparative study of the several suggestions introduced in the literature, and point out their advantages and limitations. The concepts are illustrated by simple examples as well as by empirical data of the world trade and weighted coauthorship networks.
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Social Network Analysis: Methods and Applications
Wasserman, S., & Faust, K. (1994) · doi:10.1017/cbo9780511815478 · Cited by 17,557
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Self-citationMapping Human Whole-Brain Structural Networks with Diffusion MRI
Hagmann, P., Kurant, M., Gigandet, X., Thiran, P., Wedeen, V. J., Meuli, R., & Thiran, J.-P. (2007) · PLoS ONE · doi:10.1371/journal.pone.0000597 · Cited by 788
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Colon-Perez, L. M., Ibanez, K. R., Suarez, M., Torroella, K., Acuna, K., Ofori, E., Levites, Y., Vaillancourt, D. E., Golde, T. E., Chakrabarty, P., et al. (2019) · NeuroImage · doi:10.1016/j.neuroimage.2019.116138 · Cited by 41
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Metadata
- Authors
- Saramäki, J., Kivelä, M., Onnela, J.-P., Kaski, K., & Kertész, J.
- Venue
- Physical Review E
- Publisher
- American Physical Society (APS)
- Published
- 2007-02-23
- Volume
- 75
- Issue
- 2
- Pages
- 027105-027105
- ISSN
- 1539-3755 (ISSN-L)
- 1550-2376
- OpenAlex
- W2004824191
- Cited by
- 725
- References
- 1
- FWCI
- 10.13
- Type
- journal article
- Language
- en
- Open access
- green
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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