law_firm — Lazega law firm network
- Description
A multiplex network of relationships among the 71 lawyers (36 partners and 35 associates) of a corporate law firm in New England (USA), collected by E. Lazega with questionnaires and interviews in 1988-1991, as part of his study of cooperation among peers. The version here is distributed by M. De Domenico, and has three directed layers, in which an edge $(i, j)$ means that lawyer $i$ named lawyer $j$ in response to the corresponding question:
- advice (892 edges): $i$ goes to $j$ for basic professional advice;
- friendship (575 edges): $i$ socializes with $j$ outside work;
- co-work (1,104 edges): $i$ has worked with $j$ (e.g. on a case).
The network has the following properties:
nodeStatus: 1 = partner, 2 = associate.nodeGender: 1 = man, 2 = woman.nodeOffice: office location: 1 = Boston, 2 = Hartford, 3 = Providence.nodeSeniority: number of years with the firm.nodeAge: age, in years.nodePractice: 1 = litigation, 2 = corporate law.nodeLawSchool: law school attended: 1 = Harvard or Yale, 2 = University of Connecticut, 3 = other.layer(edges): 1 = advice, 2 = friendship, 3 = co-work; the graph propertylayer_keymaps these numbers to layer names.weight(edges): always 1.
- Tags
- Social Offline Multilayer Unweighted
- Citation
-
- Emmanuel Lazega, "The Collegial Phenomenon: The Social Mechanisms of Cooperation Among Peers in a Corporate Law Partnership". Oxford University Press (2001) elazega.fr
- Upstream URL OK
- https://manliodedomenico.com/data.php
- Upstream license
- Open Data Commons Open Database License (ODbL), https://opendatacommons.org/licenses/odbl/
- Networks
-
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
Name Nodes Edges $\left<k\right>$ $\sigma_k$ $\lambda_h$ $\tau$ $r$ $c$ $\oslash$ $S$ Kind Mode NPs EPs gt GraphML GML csv law_firm 71 2,571 36.21 30.92 30.35 2.09 0.02 0.60 3 1.00 Directed Unipartite name nodeStatus nodeGender nodeOffice nodeSeniority nodeAge nodePractice nodeLawSchool weight layer 4 KiB 10 KiB 10 KiB 8 KiB - Ridiculograms*
-