dutch_school — Dutch school friendships (2003)

Description

Friendship networks among the 26 pupils of a school class (class "12b") in the first year of secondary school in the Netherlands, collected by A. Knecht in 2003–2004 for her PhD research on friendship dynamics in early adolescence, and used by T. A. B. Snijders, G. G. van de Bunt and C. E. G. Steglich to illustrate stochastic actor-oriented models. Friendship nominations were surveyed four times (waves 1 to 4), at intervals of three months. Nodes are pupils, and a directed edge $i \to j$ means that pupil $i$ nominated pupil $j$ as a friend. The same pupils are present in all networks, in the same order.

The networks are:

klas12b-net-1 to klas12b-net-4: friendships in each of the four waves;
klas12b-net-3m and klas12b-net-4m: variants of waves 3 and 4 in which all missing values are coded as 9 (their purpose is not documented in the source);
klas12b-primary: friendships in primary school, as reported in the first wave.

In the source data, missing values are coded with 9 (incidentally missing nominator) or 10 (structurally missing nominator or nominee, e.g. a pupil who left the class); these entries are not represented as edges.

The networks have the following node properties (in the attributes, 0 denotes a missing value):

missing: whether the nominations of the pupil are missing in the network.
sex (1: female, 2: male), age (in years, at wave 1), ethnicity (1: Dutch, 2: other) and religion (of the father; 1: Christian, 2: non-religious, 3: other religion).
advice: the school advice at the end of primary school (from 4, low, to 8, high).
delinquency: a scale of minor delinquency in waves 1 to 4 (1: never, 2: once, 3: 2–4 times, 4: 5–10 times, 5: more than 10 times).
alcohol: alcohol consumption in waves 2 to 4 (same scale as delinquency).
present: the first and last waves in which the pupil was present in the class.

Tags

Social Offline Unweighted Metadata Temporal

Added

2020-08-11

Citation

T. Snijders, G. van de Bunt, and C. Steglich, "Introduction to stochastic actor-based models for network dynamics." Social Networks 32(1), 44-60 (2010) 10.1016/j.socnet.2009.02.004 Sci-Hub

Upstream URL OK

http://www.stats.ox.ac.uk/~snijders/siena/tutorial2010_data.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	EPs	gt	GraphML	GML	csv
klas12b-net-1	26	91	3.50	3.33	5.52	13.60	0.35	0.51	7	1.00	Directed	Unipartite	weight	1 KiB	1 KiB	1 KiB	1 KiB
klas12b-net-2	26	144	5.54	6.71	9.33	2.85	-0.09	0.55	2	1.00	Directed	Unipartite	weight	1 KiB	1 KiB	1 KiB	1 KiB
klas12b-net-3	26	234	9.00	9.62	13.96	1.38	-0.25	0.64	2	1.00	Directed	Unipartite	weight	1 KiB	2 KiB	1 KiB	1 KiB
klas12b-net-3m	26	234	9.00	9.62	13.96	1.38	-0.25	0.64	2	1.00	Directed	Unipartite	weight	1 KiB	2 KiB	1 KiB	1 KiB
klas12b-net-4	26	170	6.54	9.10	9.53	1.81	-0.23	0.47	2	1.00	Directed	Unipartite	weight	1 KiB	2 KiB	1 KiB	1 KiB
klas12b-net-4m	26	170	6.54	9.10	9.53	1.81	-0.23	0.47	2	1.00	Directed	Unipartite	weight	1 KiB	2 KiB	1 KiB	1 KiB
klas12b-primary	26	87	3.35	5.36	6.85	0.50	0.87	0.87	2	0.35	Directed	Unipartite	weight	1 KiB	1 KiB	1 KiB	1 KiB

Ridiculograms^*

klas12b-primary drawing — klas12b-primary

^* 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.