network_science_book — Phone call, email, metabolic and citation networks of the Network Science book

Description

Four of the ten networks distributed with the textbook "Network Science" by A.-L. Barabási, which uses them throughout as reference data sets (e.g. in its Table 2.1). In all of them, nodes are anonymous and labeled consecutively from zero (the labels are the node indices), and there are no node or edge attributes. The networks are:

phonecalls: mobile phone calls among a sample of the most active users of the data set of C. Song, Z. Qu, N. Blumm and A.-L. Barabási (2010), who used the call records of about 10 million anonymized subscribers of a mobile phone carrier to study the predictability of human mobility; the data were provided by C. Song. Nodes are phone users, and a directed edge $i \to j$ means that $i$ called $j$ at least once during the observation period (the dates and the carrier are not given). The book's data page describes the edges as undirected ("called each other at least once"), but the file lists 91,826 ordered pairs (34,973 of the 56,853 connected pairs in both directions), the number of directed links given in the book's Table 2.1; the network is therefore stored as directed.
email: email traffic at the University of Kiel, Germany, collected over 112 days from the log files of the university's mail server by H. Ebel, L.-I. Mielsch and S. Bornholdt (2002). Nodes are email addresses (of the university and outside it), and a directed edge $i \to j$ means that $i$ sent at least one email to $j$. The 648 self-loops (addresses that sent emails to themselves) are kept.
metabolic: the metabolism of the bacterium Escherichia coli, derived from a metabolic reconstruction of the BiGG knowledgebase (J. Schellenberger et al., 2010); which reconstruction and version were used is not documented. Nodes are metabolites, and a directed edge $i \to j$ means that there is a reaction in which $i$ is an input (substrate) and $j$ a product. The metabolite names are not included.
citation: citations among the papers of the journals of the American Physical Society (APS): Physical Review Letters, Physical Review (its series A to E and earlier) and Reviews of Modern Physics, derived from the citation data that the APS makes available to researchers on request (S. Redner, 2005); the range of years is not documented. Nodes are papers, and a directed edge $i \to j$ means that paper $i$ cites paper $j$. The 118 self-loops and the 3,903 pairs of papers that cite each other are kept. The network is distributed here as it is in the book's data set.

The other networks of the book's data set are already in this catalog and are not repeated here: the actor network (imdb_actors_2004), the condensed matter collaboration network (CondMat of arxiv_authors, from SNAP), the Internet router network (skitter_routers_2003, with the same 192,244 nodes and 609,066 edges), the power grid (power), the yeast protein interactions of Yu et al. (2008) (y2h_union of yeast_interactome_ccsb), and the WWW network of Notre Dame (notre_dame_web).

The networks have no properties besides the node indices.

Tags

Social Communication Biological Metabolic Informational Citation Unweighted

Citation

A.-L. Barabási, "Network Science." Cambridge University Press (2016). networksciencebook.com
C. Song, Z. Qu, N. Blumm, and A.-L. Barabási, "Limits of predictability in human mobility." Science 327(5968), 1018-1021 (2010). 10.1126/science.1177170 Sci-Hub
H. Ebel, L.-I. Mielsch, and S. Bornholdt, "Scale-free topology of e-mail networks." Physical Review E 66, 035103 (2002). 10.1103/PhysRevE.66.035103 Sci-Hub
J. Schellenberger, J. O. Park, T. M. Conrad, and B. Ø. Palsson, "BiGG: a Biochemical Genetic and Genomic knowledgebase of large scale metabolic reconstructions." BMC Bioinformatics 11, 213 (2010). 10.1186/1471-2105-11-213 Sci-Hub
S. Redner, "Citation statistics from 110 years of Physical Review." Physics Today 58(6), 49-54 (2005). 10.1063/1.1996475 Sci-Hub

Upstream URL OK

https://networksciencebook.com/translations/en/resources/data.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	gt	GraphML	GML	csv
phonecalls	36,595	91,826	2.51	4.47	13.01	311.15	0.28	0.18	31	0.83	Directed	Unipartite	753 KiB	1.1 MiB	1.0 MiB	903 KiB
email	57,194	103,731	1.81	36.05	64.78	176.88	-0.08	0.00	10	0.99	Directed	Unipartite	1.0 MiB	1.5 MiB	1.4 MiB	1.2 MiB
metabolic	1,039	5,802	5.58	37.60	36.08	4.39	-0.22	0.05	6	1.00	Directed	Unipartite	25 KiB	38 KiB	37 KiB	33 KiB
citation	449,673	4,689,479	10.43	31.95	101.44	112.50	-0.02	0.08	20	1.00	Directed	Unipartite	15.4 MiB	26.2 MiB	26.4 MiB	25.3 MiB

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.