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Sound–meaning association biases evidenced across thousands of languages

Overview of attention for article published in Proceedings of the National Academy of Sciences of the United States of America, September 2016
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  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (99th percentile)
  • High Attention Score compared to outputs of the same age and source (99th percentile)

Mentioned by

news
108 news outlets
blogs
11 blogs
twitter
200 tweeters
facebook
10 Facebook pages
googleplus
5 Google+ users
reddit
2 Redditors

Readers on

mendeley
185 Mendeley
citeulike
1 CiteULike
Title
Sound–meaning association biases evidenced across thousands of languages
Published in
Proceedings of the National Academy of Sciences of the United States of America, September 2016
DOI 10.1073/pnas.1605782113
Pubmed ID
Authors

Damián E. Blasi, Søren Wichmann, Harald Hammarström, Peter F. Stadler, Morten H. Christiansen

Abstract

It is widely assumed that one of the fundamental properties of spoken language is the arbitrary relation between sound and meaning. Some exceptions in the form of nonarbitrary associations have been documented in linguistics, cognitive science, and anthropology, but these studies only involved small subsets of the 6,000+ languages spoken in the world today. By analyzing word lists covering nearly two-thirds of the world's languages, we demonstrate that a considerable proportion of 100 basic vocabulary items carry strong associations with specific kinds of human speech sounds, occurring persistently across continents and linguistic lineages (linguistic families or isolates). Prominently among these relations, we find property words ("small" and i, "full" and p or b) and body part terms ("tongue" and l, "nose" and n). The areal and historical distribution of these associations suggests that they often emerge independently rather than being inherited or borrowed. Our results therefore have important implications for the language sciences, given that nonarbitrary associations have been proposed to play a critical role in the emergence of cross-modal mappings, the acquisition of language, and the evolution of our species' unique communication system.

Twitter Demographics

The data shown below were collected from the profiles of 200 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 185 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 8 4%
United States 6 3%
Germany 4 2%
France 4 2%
Japan 3 2%
Canada 2 1%
India 2 1%
Estonia 1 <1%
Denmark 1 <1%
Other 5 3%
Unknown 149 81%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 48 26%
Researcher 39 21%
Student > Master 19 10%
Professor 16 9%
Student > Doctoral Student 15 8%
Other 48 26%
Readers by discipline Count As %
Linguistics 43 23%
Psychology 42 23%
Agricultural and Biological Sciences 23 12%
Neuroscience 17 9%
Computer Science 9 5%
Other 51 28%

Attention Score in Context

This research output has an Altmetric Attention Score of 1091. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 26 January 2018.
All research outputs
#1,829
of 9,051,505 outputs
Outputs from Proceedings of the National Academy of Sciences of the United States of America
#64
of 48,730 outputs
Outputs of similar age
#152
of 256,973 outputs
Outputs of similar age from Proceedings of the National Academy of Sciences of the United States of America
#4
of 968 outputs
Altmetric has tracked 9,051,505 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 99th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 48,730 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 25.8. This one has done particularly well, scoring higher than 99% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 256,973 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 99% of its contemporaries.
We're also able to compare this research output to 968 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 99% of its contemporaries.