Lewis Carroll's Doublets net of English words: network heterogeneity in a complex system.
Lewis Carroll's English word game Doublets is represented as a system of networks with each node being an English word and each connectivity edge confirming that its two ending words are equal in letter length, but different by exactly one letter. We show that this system, which we call the Dou...
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doaj-fba3b1b668634fd593ae1e34aad153e82020-11-25T01:25:35ZengPublic Library of Science (PLoS)PLoS ONE1932-62032014-01-01912e11417710.1371/journal.pone.0114177Lewis Carroll's Doublets net of English words: network heterogeneity in a complex system.Hsieh FushingChen ChenYin-Chen HsiehPatrick FarrellLewis Carroll's English word game Doublets is represented as a system of networks with each node being an English word and each connectivity edge confirming that its two ending words are equal in letter length, but different by exactly one letter. We show that this system, which we call the Doublets net, constitutes a complex body of linguistic knowledge concerning English word structure that has computable multiscale features. Distributed morphological, phonological and orthographic constraints and the language's local redundancy are seen at the node level. Phonological communities are seen at the network level. And a balancing act between the language's global efficiency and redundancy is seen at the system level. We develop a new measure of intrinsic node-to-node distance and a computational algorithm, called community geometry, which reveal the implicit multiscale structure within binary networks. Because the Doublets net is a modular complex cognitive system, the community geometry and computable multi-scale structural information may provide a foundation for understanding computational learning in many systems whose network structure has yet to be fully analyzed.http://europepmc.org/articles/PMC4269387?pdf=render |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Hsieh Fushing Chen Chen Yin-Chen Hsieh Patrick Farrell |
spellingShingle |
Hsieh Fushing Chen Chen Yin-Chen Hsieh Patrick Farrell Lewis Carroll's Doublets net of English words: network heterogeneity in a complex system. PLoS ONE |
author_facet |
Hsieh Fushing Chen Chen Yin-Chen Hsieh Patrick Farrell |
author_sort |
Hsieh Fushing |
title |
Lewis Carroll's Doublets net of English words: network heterogeneity in a complex system. |
title_short |
Lewis Carroll's Doublets net of English words: network heterogeneity in a complex system. |
title_full |
Lewis Carroll's Doublets net of English words: network heterogeneity in a complex system. |
title_fullStr |
Lewis Carroll's Doublets net of English words: network heterogeneity in a complex system. |
title_full_unstemmed |
Lewis Carroll's Doublets net of English words: network heterogeneity in a complex system. |
title_sort |
lewis carroll's doublets net of english words: network heterogeneity in a complex system. |
publisher |
Public Library of Science (PLoS) |
series |
PLoS ONE |
issn |
1932-6203 |
publishDate |
2014-01-01 |
description |
Lewis Carroll's English word game Doublets is represented as a system of networks with each node being an English word and each connectivity edge confirming that its two ending words are equal in letter length, but different by exactly one letter. We show that this system, which we call the Doublets net, constitutes a complex body of linguistic knowledge concerning English word structure that has computable multiscale features. Distributed morphological, phonological and orthographic constraints and the language's local redundancy are seen at the node level. Phonological communities are seen at the network level. And a balancing act between the language's global efficiency and redundancy is seen at the system level. We develop a new measure of intrinsic node-to-node distance and a computational algorithm, called community geometry, which reveal the implicit multiscale structure within binary networks. Because the Doublets net is a modular complex cognitive system, the community geometry and computable multi-scale structural information may provide a foundation for understanding computational learning in many systems whose network structure has yet to be fully analyzed. |
url |
http://europepmc.org/articles/PMC4269387?pdf=render |
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