advogato — Advogato trust network (2014)

Description

A network of trust relationships among users of Advogato, an online community platform for free software developers launched in 1999. On Advogato, users certify each other at one of the levels Apprentice, Journeyer and Master, and these certifications are used by the site's trust metric to compute the users' own levels; a certification at the level Observer is equivalent to no trust. Advogato published the whole certification graph at www.advogato.org/person/graph.dot, and the Trustlet project (P. Massa and collaborators) downloaded a daily snapshot of it between 2007 and 2014 (together with older snapshots from 2000 onwards). This network is the last such snapshot, taken on 7 July 2014.

Nodes are all users listed in the file, including those who neither give nor receive any certification (almost half of them), and a directed edge from $i$ to $j$ means that user $i$ certified user $j$. Users can certify themselves, so the network has self-loops, and the source file lists 15 certifications twice.

The network has the following properties:

Nodes: name, the Advogato user name.
Edges: level, the certification level (Observer, Apprentice, Journeyer or Master); weight, the numerical trust value 0.4, 0.6, 0.8 or 1.0 of these levels, following the mapping suggested by Trustlet for the last three.

Tags

Social Online Weighted

Citation

P. Massa, M. Salvetti, and D. Tomasoni. "Bowling alone and trust decline in social network sites." Dependable, Autonomic and Secure Computing, 2009. DASC'09. Eighth IEEE International Conference on. (2009). 10.1109/dasc.2009.130 Sci-Hub

Upstream URL OK

https://web.archive.org/web/20150610220637/http://www.trustlet.org/wiki/Advogato_dataset

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
advogato	6,541	51,127	7.82	34.13	68.61	20.71	-0.05	0.11	9	0.77	Directed	Unipartite	meta	weight	240 KiB	416 KiB	405 KiB	305 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.