Space-Independent Community Structure Detection in United States Air Transportation

Gegov, Emil; Gegov, Alexander; Postorino, Maria Nadia; Atherton, Mark; Gobet, Fernand

doi:10.3182/20120912-3-bg-2031.00001

Cited by 2 publications

(1 citation statement)

References 12 publications

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“…Applying complex network models to study the dynamic features of language systems has become popular in recent years in fields such as language evolution/change and language development [ 2 , 28 , 29 ], quantitative linguistics [ 30 , 31 , 32 , 33 , 34 ], and language acquisition [ 21 , 35 , 36 ]. With regard to word co-occurrence networks, there have been many studies [ 29 , 30 , 35 , 37 – 39 ].…”

Section: Introductionmentioning

confidence: 99%

How does language change as a lexical network? An investigation based on written Chinese word co-occurrence networks

Chen

Liu

2018

PLoS ONE

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Language is a complex adaptive system, but how does it change? For investigating this process, four diachronic Chinese word co-occurrence networks have been built based on texts that were written during the last 2,000 years. By comparing the network indicators that are associated with the hierarchical features in language networks, we learn that the hierarchy of Chinese lexical networks has indeed evolved over time at three different levels. The connections of words at the micro level are continually weakening; the number of words in the meso-level communities has increased significantly; and the network is expanding at the macro level. This means that more and more words tend to be connected to medium-central words and form different communities. Meanwhile, fewer high-central words link these communities into a highly efficient small-world network. Understanding this process may be crucial for understanding the increasing structural complexity of the language system.

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