↓ Skip to main content

Statistical Image Properties in Large Subsets of Traditional Art, Bad Art, and Abstract Art

Overview of attention for article published in Frontiers in Neuroscience, October 2017
Altmetric Badge

About this Attention Score

  • Good Attention Score compared to outputs of the same age (65th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (61st percentile)

Mentioned by

twitter
7 X users

Citations

dimensions_citation
22 Dimensions

Readers on

mendeley
30 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Statistical Image Properties in Large Subsets of Traditional Art, Bad Art, and Abstract Art
Published in
Frontiers in Neuroscience, October 2017
DOI 10.3389/fnins.2017.00593
Pubmed ID
Authors

Christoph Redies, Anselm Brachmann

Abstract

Several statistical image properties have been associated with large subsets of traditional visual artworks. Here, we investigate some of these properties in three categories of art that differ in artistic claim and prestige: (1) Traditional art of different cultural origin from established museums and art collections (oil paintings and graphic art of Western provenance, Islamic book illustration and Chinese paintings), (2) Bad Art from two museums that collect contemporary artworks of lesser importance (© Museum Of Bad Art [MOBA], Somerville, and Official Bad Art Museum of Art [OBAMA], Seattle), and (3) twentieth century abstract art of Western provenance from two prestigious museums (Tate Gallery and Kunstsammlung Nordrhein-Westfalen). We measured the following four statistical image properties: the fractal dimension (a measure relating to subjective complexity); self-similarity (a measure of how much the sections of an image resemble the image as a whole), 1st-order entropy of edge orientations (a measure of how uniformly different orientations are represented in an image); and 2nd-order entropy of edge orientations (a measure of how independent edge orientations are across an image). As shown previously, traditional artworks of different styles share similar values for these measures. The values for Bad Art and twentieth century abstract art show a considerable overlap with those of traditional art, but we also identified numerous examples of Bad Art and abstract art that deviate from traditional art. By measuring statistical image properties, we quantify such differences in image composition for the first time.

X Demographics

X Demographics

The data shown below were collected from the profiles of 7 X users who shared this research output. Click here to find out more about how the information was compiled.
As of 1 July 2024, you may notice a temporary increase in the numbers of X profiles with Unknown location. Click here to learn more.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 30 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 30 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 8 27%
Student > Bachelor 5 17%
Student > Master 4 13%
Professor > Associate Professor 3 10%
Professor 3 10%
Other 5 17%
Unknown 2 7%
Readers by discipline Count As %
Psychology 12 40%
Computer Science 4 13%
Social Sciences 3 10%
Neuroscience 2 7%
Design 2 7%
Other 5 17%
Unknown 2 7%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 30 December 2017.
All research outputs
#7,736,922
of 26,367,306 outputs
Outputs from Frontiers in Neuroscience
#5,011
of 11,814 outputs
Outputs of similar age
#114,568
of 342,678 outputs
Outputs of similar age from Frontiers in Neuroscience
#67
of 181 outputs
Altmetric has tracked 26,367,306 research outputs across all sources so far. This one has received more attention than most of these and is in the 69th percentile.
So far Altmetric has tracked 11,814 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 11.3. This one has gotten more attention than average, scoring higher than 57% 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 342,678 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 65% of its contemporaries.
We're also able to compare this research output to 181 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 61% of its contemporaries.