thurman_office — Thurman office networks (1979)
- Description
Relations among 15 employees of the overseas office of a large international corporation, observed by B. Thurman during 16 months, in which two major disputes erupted in this subgroup. Thurman analyzed the outcome of the disputes in terms of the network of formal and informal associations among those involved. The data were distributed in UCINET format (from the UCINET data collection of S. P. Borgatti, M. G. Everett and L. C. Freeman) on the Pajek datasets page of V. Batagelj and A. Mrvar, from which this version was obtained.
formal: the formal organizational chart (THURA), as directed edges between employees (from the row to the column of the source matrix). The direction is not documented, but the edges appear to go from a superior to a subordinate (e.g. the president has an edge to every other employee).multiplex: the employees linked by multiplex (informal) ties (THURM).
The networks have the following properties:
- Nodes:
name, the (pseudonymous) name or position of the employee.
- Tags
- Social Offline Unweighted Metadata
- Citation
-
- B. Thurman, "In the office: Networks and coalitions." Social Networks 2(1), 47-63 (1979) 10.1016/0378-8733(79)90010-8 Sci-Hub
- S. P. Borgatti, M. G. Everett, L. C. Freeman, "UCINET for Windows: Software for Social Network Analysis." Analytic Technologies, Harvard, MA (2002) web.archive.org
- Upstream URL OK
- https://web.archive.org/web/20020312110633/http://vlado.fmf.uni-lj.si/pub/networks/data/UciNet/UciData.htm
- Networks
-
Tip: click on a column header to sort the list, or hover over it 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
Name Nodes Edges $\left<k\right>$ $\sigma_k$ $\lambda_h$ $\tau$ $r$ $c$ $\oslash$ $S$ Kind Mode NPs EPs gt GraphML GML csv formal 15 34 2.27 3.90 4.82 1.22 -0.71 0.35 2 1.00 Directed Unipartite name 1 KiB 1 KiB 1 KiB 1 KiB multiplex 15 33 4.40 2.44 4.61 2.39 -0.30 0.52 3 1.00 Undirected Unipartite name 1 KiB 1 KiB 1 KiB 1 KiB - Ridiculograms*