sawmill — Sawmill communication network (1997)
- Description
Communication ties among the 36 employees of a small enterprise, a sawmill, studied by J. H. Michael and J. G. Massey. All employees were asked to indicate the frequency with which they discussed work matters with each of their colleagues, on a five-point scale ranging from less than once a week to several times a day, and two employees are connected if they rated their contact as three or more (it is not known whether both employees, or at least one of them, had to rate the tie in this way). The employees are Spanish-speaking (Hispanic) or English-speaking, and work in the two main sections of the sawmill: the mill, where tree trunks are sawn into logs, and the planer section, where logs are planed; two employees work in the yard, and there are some managers and additional officials. 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, a label that encodes the language and section of the employee: the first letter is H (Hispanic) or E (English-speaking), followed by the section, M (mill) or P (planer), and a number (e.g. "HP-10" is a Hispanic employee working in the planer section); Y-1 and Y-2 work in the yard, and the other labels give the position of the managers and officials (e.g. "Owner", "Forester").
- Nodes:
- Tags
- Social Offline Unweighted Metadata
- Citation
-
- J. H. Michael, J. G. Massey, "Modeling the communication network in a sawmill." Forest Products Journal 47(9), 25-30 (1997) web.archive.org
- W. de Nooy, A. Mrvar, V. Batagelj, "Exploratory Social Network Analysis with Pajek." Cambridge University Press (2005) 10.1017/CBO9780511806452 Sci-Hub
- Upstream URL OK
- https://web.archive.org/web/20040706125343/http://vlado.fmf.uni-lj.si/pub/networks/data/esna/sawmill.htm
- Networks
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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