centrality_literature — Centrality literature citations (1948-1979)
- Description
Citations among 129 publications on network centrality between 1948 and 1979, from the study of N. P. Hummon, P. Doreian and L. C. Freeman of the centrality-productivity literature that preceded (and includes) Freeman's 1979 paper on centrality. Edges represent citations and point from the cited to the citing paper. Papers citing one another (e.g. papers by the same author appearing at about the same time) were shrunk into a single node, so the network is acyclic. The data were distributed on the Pajek datasets page of the book Exploratory Social Network Analysis with Pajek (de Nooy, Mrvar and Batagelj), from which this version was obtained.
The network has the following properties:
- Nodes:
name, the label of the publication (author and the last two digits of the publication year);year, the year of publication. - Edges:
weight, 1 for a regular citation, or 2 for a double citation (when the citing or the cited paper is a node combining two papers that cite each other).
- Nodes:
- Tags
- Informational Citation Weighted Metadata
- Citation
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- N. P. Hummon, P. Doreian, L. C. Freeman, "Analyzing the Structure of the Centrality-Productivity Literature Created Between 1948 and 1979." Knowledge 11(4), 459-480 (1990) 10.1177/107554709001100405 Sci-Hub
- W. de Nooy, A. Mrvar, V. Batagelj, "Exploratory Social Network Analysis with Pajek." Cambridge University Press (2005) 10.1017/CBO9780511806452 Sci-Hub
- Upstream URL [Errno 111] Connection refused
- https://web.archive.org/web/20040528213143/http://vlado.fmf.uni-lj.si/pub/networks/data/esna/centrality.htm
- Networks
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Tip: hover over a column header for a description.
Column legend
- $\left<k\right>$
- Mean degree
- $\sigma_k$
- Standard deviation of the degrees
- $\lambda_h$
- Largest eigenvalue of the Hashimoto (non-backtracking) matrix
- $\tau$
- Random walk mixing time
- $r$
- Degree assortativity
- $c$
- Global clustering coefficient
- $\oslash$
- (Pseudo-) diameter
- $S$
- Relative size of the largest component
- NPs
- Node properties
- EPs
- Edge properties