unicodelang — Languages spoken by country (2015)

Description

A bipartite network of territories (countries and other territories with their own ISO 3166 code) and the languages spoken in them, from the territory–language information of the Unicode Common Locale Data Repository (CLDR), version 27 (released in March 2015). The CLDR collects these figures, with references to their sources, to estimate the number of users of each language in each territory; it aims at approximate figures for the literate, functional population of each language, i.e. the people able to read and write the language and comfortable enough to use it with computers. Each edge connects a territory with a language and is weighted by the percentage of the population of the territory that uses the language. Languages are identified by their CLDR (BCP 47) codes; where the data distinguish the scripts in which a language is written (e.g. uz_Arab and uz for Uzbek in Arabic and in the default script), these are separate nodes. The pseudo-territory "Unknown Region" (ZZ), which has no data, is not included, and Antarctica and Bouvet Island are connected only to the "unknown language" node (und).

The network has the following properties:

(Node) is_language: whether the node is a language (otherwise it is a territory).
(Node) code: the CLDR code of the language or territory.
(Node) name: its English name, from the CLDR English locale data.
(Node) population, gdp and literacy_percent: the population, the gross domestic product (in US dollars) and the literacy rate (in percent) of the territory, as given in the CLDR (territories only; NaN for languages).
(Edge) population_percent: the percentage of the territory's population using the language.
(Edge) writing_percent: the percentage of these that also write the language, where given (NaN otherwise).
(Edge) official_status: the official status of the language in the territory (official, de_facto_official, official_regional, or empty if none).

Tags

Informational Relatedness Weighted Metadata

Added

2020-08-11

Citation

Unicode Consortium, "Unicode Common Locale Data Repository (CLDR), version 27." (2015) www.unicode.org

Upstream URL OK

https://cldr.unicode.org/index/downloads

Upstream license

Unicode License Agreement, https://www.unicode.org/license.txt

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
unicodelang	868	1,255	2.89	6.73	7.88	25.78	-0.17	0.00	8	0.99	Undirected	Bipartite	meta	weight	19 KiB	26 KiB	25 KiB	19 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.