Evidence map›Paper›PMID 36107963›Full record

ArticlePloS one2022

A multiplex analysis of phonological and orthographic networks.

Pablo Lara-Martínez, Bibiana Obregón-Quintana, C F Reyes-Manzano, Irene López-Rodríguez, Lev Guzmán-Vargas

Abstract read
In one paragraph

Article in PloS one, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors.

Pablo Lara-MartínezFacultad de Ciencias, Universidad Nacional Autónoma de México, Ciudad de México, México.ORCID 0000-0002-5909-9194
Bibiana Obregón-QuintanaFacultad de Ciencias, Universidad Nacional Autónoma de México, Ciudad de México, México.
C F Reyes-ManzanoTecnológico Nacional de México, Tecnológico de Estudios Superiores de Ixtapaluca, Ixtapaluca, Estado de México, México.
Irene López-RodríguezUnidad Profesional Interdisciplinaria en Ingeniería y Tecnologías Avanzadas, Instituto Politécnico Nacional, Ciudad de México, México.
Lev Guzmán-VargasUnidad Profesional Interdisciplinaria en Ingeniería y Tecnologías Avanzadas, Instituto Politécnico Nacional, Ciudad de México, México.ORCID 0000-0003-3098-8796

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The study of natural language using a network approach has made it possible to characterize novel properties ranging from the level of individual words to phrases or sentences. A natural way to quantitatively evaluate similarities and differences between spoken and written language is by means of a multiplex network defined in terms of a similarity distance between words. Here, we use a multiplex representation of words based on orthographic or phonological similarity to evaluate their structure. We report that from the analysis of topological properties of networks, there are different levels of local and global similarity when comparing written vs. spoken structure across 12 natural languages from 4 language families. In particular, it is found that differences between the phonetic and written layers is markedly higher for French and English, while for the other languages analyzed, this separation is relatively smaller. We conclude that the multiplex approach allows us to explore additional properties of the interaction between spoken and written language.

Indexed as

LanguagePhoneticsHumans

Identifiers

PMID36107963
PMCPMC9477335

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.