student_government — Ljubljana student government communication (1992)

Description

Communication relations among the members and advisors of the Student Government of the University of Ljubljana (Slovenia), collected by V. Hlebec in May 1992 in an experiment comparing two methods of collecting network data: recall, in which respondents named the members of their egocentric networks from memory, and recognition, in which they were given a list of all members and selected those they communicate with (most often). The number of listed persons was not limited in either method. Communication flow was identified by three questions, referring to the matters of the Student Government during the six months since its formation: "Who of the members and advisors of the Student Government do you (most often) informally discuss with?", "Which members and advisors do you (most often) ask for an opinion?", and "Which members and advisors (most often) ask you for an opinion?". One of the twelve members refused to cooperate, so the networks have 11 actors. The data reflect the actors' cognition of the communication, rather than observed interactions. The data were distributed in Pajek format on the Pajek datasets page of V. Batagelj and A. Mrvar, from which this version was obtained.

discussion_recall, discussion_recognition: informal discussion, from the respondent to the person named.
ask_recall, ask_recognition: asking for an opinion, from the respondent to the person named.
asked_recall, asked_recognition: being asked for an opinion; the matrices were transposed in the source, so that an edge points from the person who asks for an opinion to the respondent who reported it.

The networks have the following properties:

Nodes: name, the position of the actor (prime minister, ministers 1 to 7, and advisers 1 to 3).

Tags

Social Communication Unweighted Metadata

Citation

V. Hlebec, "Recall versus recognition: Comparison of the two alternative procedures for collecting social network data." In A. Ferligoj, A. Kramberger (eds.), Developments in Statistics and Methodology, Metodološki zvezki 9, FDV, Ljubljana (1993), pp. 121-129 dk.fdv.uni-lj.si

Upstream URL OK

https://web.archive.org/web/20040115070328/http://vlado.fmf.uni-lj.si/pub/networks/data/soc/Tina/Tina.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	gt	GraphML	GML	csv
discussion_recall	11	41	3.73	2.27	5.16	1.59	-0.04	0.61	3	1.00	Directed	Unipartite	name	1 KiB	1 KiB	1 KiB	1 KiB
discussion_recognition	11	48	4.36	2.05	5.89	1.52	-0.15	0.66	3	1.00	Directed	Unipartite	name	1 KiB	1 KiB	1 KiB	1 KiB
ask_recall	11	29	2.64	1.81	3.88	2.43	-0.06	0.47	3	1.00	Directed	Unipartite	name	1 KiB	1 KiB	1 KiB	1 KiB
ask_recognition	11	36	3.27	1.92	4.29	2.49	-0.21	0.51	3	1.00	Directed	Unipartite	name	1 KiB	1 KiB	1 KiB	1 KiB
asked_recall	11	41	3.73	3.29	4.86	1.44	-0.25	0.56	3	1.00	Directed	Unipartite	name	1 KiB	1 KiB	1 KiB	1 KiB
asked_recognition	11	42	3.82	2.53	5.17	1.70	-0.18	0.64	3	1.00	Directed	Unipartite	name	1 KiB	1 KiB	1 KiB	1 KiB