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residence_hall — ANU Residence Hall network

Description

Friendships among the 217 residents of a residence hall on the campus of the Australian National University, collected by C. M. Webster. The residents were interviewed individually at the start of the second semester: first, they were asked to recall all their friends currently living in the residence hall; then they were given a list of all the residents, and asked to add anyone else they considered a friend. Finally, they indicated the strength of each friendship tie; most specified three levels of friendship: "best friend", "close friend" and "friend". The data were combined into a valued matrix of reported friendship relations. The data were distributed by L. C. Freeman on his network data page at the University of California, Irvine (no longer online), from which this version was obtained via the Internet Archive.

A directed edge (i, j) indicates that resident i named resident j as a friend.

The network has the following properties:

  • (Edge) weight: the strength of the friendship tie, from 1 to 5 (the source mentions the three levels above, but does not document the coding of the values; 95% of the ties have values 3 to 5).
Tags
Social Offline Weighted
Added
2020-08-11
Citation
Upstream URL OK
https://web.archive.org/web/20210115130726/http://moreno.ss.uci.edu/data.html#oz
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
residence_hall 217 2,672 12.31 11.13 20.34 5.92 0.12 0.34 4 1.00 Directed Unipartite weight 8 KiB 15 KiB 15 KiB 12 KiB
Ridiculograms*
* These are automatically generated force-directed visualizations, and can be quite meaningless for networks both big and small. They should not be taken seriously as sources of scientific insight. See here for a discussion.