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Statistical and methodological problems with concreteness and other semantic variables: A list memory experiment case study

Overview of attention for article published in Behavior Research Methods, July 2017
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Title
Statistical and methodological problems with concreteness and other semantic variables: A list memory experiment case study
Published in
Behavior Research Methods, July 2017
DOI 10.3758/s13428-017-0938-y
Pubmed ID
Authors

Lewis Pollock

Abstract

The purpose of this article is to highlight problems with a range of semantic psycholinguistic variables (concreteness, imageability, individual modality norms, and emotional valence) and to provide a way of avoiding these problems. Focusing on concreteness, I show that for a large class of words in the Brysbaert, Warriner, and Kuperman (Behavior Research Methods 46: 904-911, 2013) concreteness norms, the mean concreteness values do not reflect the judgments that actual participants made. This problem applies to nearly every word in the middle of the concreteness scale. Using list memory experiments as a case study, I show that many of the "abstract" stimuli in concreteness experiments are not unequivocally abstract. Instead, they are simply those words about which participants tend to disagree. I report three replications of list memory experiments in which the contrast between concrete and abstract stimuli was maximized, so that the mean concreteness values were accurate reflections of participants' judgments. The first two experiments did not produce a concreteness effect. After I introduced an additional control, the third experiment did produce a concreteness effect. The article closes with a discussion of the implications of these results, as well as a consideration of variables other than concreteness. The sensorimotor experience variables (imageability and individual modality norms) show the same distribution as concreteness. The distribution of emotional valence scores is healthier, but variability in ratings takes on a special significance for this measure because of how the scale is constructed. I recommend that researchers using these variables keep the standard deviations of the ratings of their stimuli as low as possible.

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The data shown below were collected from the profiles of 4 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 57 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 57 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 13 23%
Researcher 6 11%
Student > Doctoral Student 6 11%
Student > Bachelor 5 9%
Student > Master 5 9%
Other 7 12%
Unknown 15 26%
Readers by discipline Count As %
Psychology 18 32%
Linguistics 6 11%
Neuroscience 5 9%
Computer Science 4 7%
Unspecified 2 4%
Other 6 11%
Unknown 16 28%
Attention Score in Context

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 31 December 2019.
All research outputs
#15,745,807
of 25,382,440 outputs
Outputs from Behavior Research Methods
#1,423
of 2,526 outputs
Outputs of similar age
#178,601
of 324,713 outputs
Outputs of similar age from Behavior Research Methods
#30
of 44 outputs
Altmetric has tracked 25,382,440 research outputs across all sources so far. This one is in the 37th percentile – i.e., 37% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2,526 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.2. This one is in the 41st percentile – i.e., 41% of its peers scored the same or lower than it.
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 324,713 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 43rd percentile – i.e., 43% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 44 others from the same source and published within six weeks on either side of this one. This one is in the 27th percentile – i.e., 27% of its contemporaries scored the same or lower than it.