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Adaptive Communication: Languages with More Non-Native Speakers Tend to Have Fewer Word Forms.

Bentz C, Verkerk A, Kiela D, Hill F, Buttery P - PLoS ONE (2015)

Bottom Line: We consider the effect of language contact-the number of non-native speakers a language has-on the way languages change and evolve.By analysing hundreds of languages within and across language families, regions, and text types, we show that languages with greater levels of contact typically employ fewer word forms to encode the same information content (a property we refer to as lexical diversity).Language evolution and change should be modeled as the co-evolution of multiple intertwined adaptive systems: On one hand, the structure of human societies and human learning capabilities, and on the other, the structure of language.

View Article: PubMed Central - PubMed

Affiliation: Department of Theoretical and Applied Linguistics, University of Cambridge, Cambridge, United Kingdom.

ABSTRACT
Explaining the diversity of languages across the world is one of the central aims of typological, historical, and evolutionary linguistics. We consider the effect of language contact-the number of non-native speakers a language has-on the way languages change and evolve. By analysing hundreds of languages within and across language families, regions, and text types, we show that languages with greater levels of contact typically employ fewer word forms to encode the same information content (a property we refer to as lexical diversity). Based on three types of statistical analyses, we demonstrate that this variance can in part be explained by the impact of non-native speakers on information encoding strategies. Finally, we argue that languages are information encoding systems shaped by the varying needs of their speakers. Language evolution and change should be modeled as the co-evolution of multiple intertwined adaptive systems: On one hand, the structure of human societies and human learning capabilities, and on the other, the structure of language.

No MeSH data available.


Word frequency distributions for English and German UDHR.Bars indicate frequencies of occurrence in German (blue) and English (red) for the highest ranking words in the UDHR text.
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pone.0128254.g001: Word frequency distributions for English and German UDHR.Bars indicate frequencies of occurrence in German (blue) and English (red) for the highest ranking words in the UDHR text.

Mentions: To scrutinize the distribution of word types in a given text they are ordered according to their frequency of occurrence. For example, Fig 1 displays the first 7 ranks of word types with their frequencies for the UDHR in German and English. Despite the constant information content of these parallel translations, English’s repetitive usage of the same word types results in high frequencies in the upper ranks. For example, the letter sequence representing the definite article in English (the) occurs roughly 120 times in the English UDHR, whereas German distributes occurrences of articles over different word types, i.e. der (ca. 60), die (ca. 50) and das (ca. 30).


Adaptive Communication: Languages with More Non-Native Speakers Tend to Have Fewer Word Forms.

Bentz C, Verkerk A, Kiela D, Hill F, Buttery P - PLoS ONE (2015)

Word frequency distributions for English and German UDHR.Bars indicate frequencies of occurrence in German (blue) and English (red) for the highest ranking words in the UDHR text.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4470635&req=5

pone.0128254.g001: Word frequency distributions for English and German UDHR.Bars indicate frequencies of occurrence in German (blue) and English (red) for the highest ranking words in the UDHR text.
Mentions: To scrutinize the distribution of word types in a given text they are ordered according to their frequency of occurrence. For example, Fig 1 displays the first 7 ranks of word types with their frequencies for the UDHR in German and English. Despite the constant information content of these parallel translations, English’s repetitive usage of the same word types results in high frequencies in the upper ranks. For example, the letter sequence representing the definite article in English (the) occurs roughly 120 times in the English UDHR, whereas German distributes occurrences of articles over different word types, i.e. der (ca. 60), die (ca. 50) and das (ca. 30).

Bottom Line: We consider the effect of language contact-the number of non-native speakers a language has-on the way languages change and evolve.By analysing hundreds of languages within and across language families, regions, and text types, we show that languages with greater levels of contact typically employ fewer word forms to encode the same information content (a property we refer to as lexical diversity).Language evolution and change should be modeled as the co-evolution of multiple intertwined adaptive systems: On one hand, the structure of human societies and human learning capabilities, and on the other, the structure of language.

View Article: PubMed Central - PubMed

Affiliation: Department of Theoretical and Applied Linguistics, University of Cambridge, Cambridge, United Kingdom.

ABSTRACT
Explaining the diversity of languages across the world is one of the central aims of typological, historical, and evolutionary linguistics. We consider the effect of language contact-the number of non-native speakers a language has-on the way languages change and evolve. By analysing hundreds of languages within and across language families, regions, and text types, we show that languages with greater levels of contact typically employ fewer word forms to encode the same information content (a property we refer to as lexical diversity). Based on three types of statistical analyses, we demonstrate that this variance can in part be explained by the impact of non-native speakers on information encoding strategies. Finally, we argue that languages are information encoding systems shaped by the varying needs of their speakers. Language evolution and change should be modeled as the co-evolution of multiple intertwined adaptive systems: On one hand, the structure of human societies and human learning capabilities, and on the other, the structure of language.

No MeSH data available.