harry_potter_support — Harry Potter peer support networks (2013)

Description

Peer support among 64 students of Hogwarts in the first six Harry Potter books by J. K. Rowling, coded by G. Bossaert and N. Meidert from the e-books, and distributed by T. Snijders with the SIENA software. Each book narrates one school year. A tie was coded when a student voluntarily gave another student one of four types of support: emotional support, instrumental help, information, or praise. Only interactions between two living students attending Hogwarts at the same time were coded. Of the 80 students mentioned in the series, 16 were excluded because the time they entered or left Hogwarts is not known. According to the authors, the networks are quite heterogeneous over time.

A directed edge (i, j) in network bookN indicates that student i supported student j in book N. The diagonal entries of the source matrices (some of which are nonzero) are ignored.

The networks have the following properties:

Nodes: name, the name of the character; schoolyear, the year the student entered Hogwarts; gender (1: male, 2: female); house (1: Gryffindor, 2: Hufflepuff, 3: Ravenclaw, 4: Slytherin); present, whether the student attended Hogwarts during the book, according to the composition change file of the data set.

Tags

Social Fictional Unweighted Metadata Temporal

Citation

G. Bossaert, N. Meidert, "'We are only as strong as we are united, as weak as we are divided'. A dynamic analysis of the peer support networks in the Harry Potter books." Open Journal of Applied Sciences 3(2), 174-185 (2013) 10.4236/ojapps.2013.32024 Sci-Hub

Upstream URL OK

https://www.stats.ox.ac.uk/~snijders/siena/HarryPotterData.html

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
book1	64	36	0.56	3.13	4.03	2.74	0.09	0.76	3	0.16	Directed	Unipartite	name schoolyear gender house present	1 KiB	2 KiB	2 KiB	2 KiB
book2	64	91	1.42	5.59	7.03	2.79	-0.25	0.65	2	0.28	Directed	Unipartite	name schoolyear gender house present	2 KiB	2 KiB	2 KiB	2 KiB
book3	64	87	1.36	5.46	6.60	2.82	-0.14	0.65	3	0.27	Directed	Unipartite	name schoolyear gender house present	2 KiB	2 KiB	2 KiB	2 KiB
book4	64	34	0.53	2.86	3.61	2.68	-0.27	0.56	3	0.19	Directed	Unipartite	name schoolyear gender house present	1 KiB	2 KiB	2 KiB	2 KiB
book5	64	133	2.08	6.67	6.54	6.35	-0.19	0.58	2	0.36	Directed	Unipartite	name schoolyear gender house present	2 KiB	2 KiB	2 KiB	2 KiB
book6	64	53	0.83	3.63	4.46	1.97	-0.19	0.45	4	0.23	Directed	Unipartite	name schoolyear gender house present	1 KiB	2 KiB	2 KiB	2 KiB