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The ageing neighbourhood: phonological density in naming

Overview of attention for article published in Language and Cognitive Processes, March 2014
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (59th percentile)
  • Average Attention Score compared to outputs of the same age and source

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2 tweeters

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23 Mendeley
Title
The ageing neighbourhood: phonological density in naming
Published in
Language and Cognitive Processes, March 2014
DOI 10.1080/01690965.2013.837495
Pubmed ID
Authors

Jean K. Gordon, Jake C. Kurczek, Gordon JK, Kurczek JC

Abstract

Aging affects the ability to retrieve words for production, despite maintainence of lexical knowledge. In this study, we investigate the influence of lexical variables on picture naming accuracy and latency in adults ranging in age from 22 to 86 years. In particular, we explored the influence of phonological neighborhood density, which has been shown to exert competitive effects on word recognition, but to facilitate word production, a finding with implications for models of the lexicon. Naming responses were slower and less accurate for older participants, as expected. Target frequency also played a strong role, with facilitative frequency effects becoming stronger with age. Neighborhood density interacted with age, such that naming was slower for high-density than low-density items, but only for older subjects. Explaining this finding within an interactive activation model suggests that, as we age, the ability of activated neighbors to facilitate target production diminishes, while their activation puts them in competition with the target.

Twitter Demographics

The data shown below were collected from the profiles of 2 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 23 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 4 17%
Australia 1 4%
United Kingdom 1 4%
Canada 1 4%
Unknown 16 70%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 7 30%
Researcher 7 30%
Student > Postgraduate 3 13%
Professor 2 9%
Student > Doctoral Student 2 9%
Other 2 9%
Readers by discipline Count As %
Psychology 10 43%
Linguistics 8 35%
Neuroscience 3 13%
Computer Science 1 4%
Medicine and Dentistry 1 4%
Other 0 0%

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 25 February 2014.
All research outputs
#2,390,106
of 6,230,816 outputs
Outputs from Language and Cognitive Processes
#81
of 186 outputs
Outputs of similar age
#51,903
of 133,516 outputs
Outputs of similar age from Language and Cognitive Processes
#4
of 8 outputs
Altmetric has tracked 6,230,816 research outputs across all sources so far. This one has received more attention than most of these and is in the 60th percentile.
So far Altmetric has tracked 186 research outputs from this source. They receive a mean Attention Score of 4.7. This one has gotten more attention than average, scoring higher than 51% 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 133,516 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 59% of its contemporaries.
We're also able to compare this research output to 8 others from the same source and published within six weeks on either side of this one. This one has scored higher than 4 of them.