| Title |
Revisiting Rossion and Pourtois with new ratings for automated complexity, familiarity, beauty, and encounter
|
|---|---|
| Published in |
Behavior Research Methods, October 2016
|
| DOI | 10.3758/s13428-016-0808-z |
| Pubmed ID | |
| Authors |
Alex Forsythe, Nichola Street, Mai Helmy |
| Abstract |
Differences between norm ratings collected when participants are asked to consider more than one picture characteristic are contrasted with the traditional methodological approaches of collecting ratings separately for image constructs. We present data that suggest that reporting normative data, based on methodological procedures that ask participants to consider multiple image constructs simultaneously, could potentially confounded norm data. We provide data for two new image constructs, beauty and the extent to which participants encountered the stimuli in their everyday lives. Analysis of this data suggests that familiarity and encounter are tapping different image constructs. The extent to which an observer encounters an object predicts human judgments of visual complexity. Encountering an image was also found to be an important predictor of beauty, but familiarity with that image was not. Taken together, these results suggest that continuing to collect complexity measures from human judgments is a pointless exercise. Automated measures are more reliable and valid measures, which are demonstrated here as predicting human preferences. |
X Demographics
The data shown below were collected from the profiles of 5 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 3 | 60% |
| Unknown | 2 | 40% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 3 | 60% |
| Scientists | 1 | 20% |
| Science communicators (journalists, bloggers, editors) | 1 | 20% |
Mendeley readers
The data shown below were compiled from readership statistics for 22 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 1 | 5% |
| Unknown | 21 | 95% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 10 | 45% |
| Student > Master | 4 | 18% |
| Student > Bachelor | 3 | 14% |
| Researcher | 2 | 9% |
| Professor | 1 | 5% |
| Other | 0 | 0% |
| Unknown | 2 | 9% |
| Readers by discipline | Count | As % |
|---|---|---|
| Psychology | 12 | 55% |
| Social Sciences | 2 | 9% |
| Linguistics | 1 | 5% |
| Medicine and Dentistry | 1 | 5% |
| Engineering | 1 | 5% |
| Other | 0 | 0% |
| Unknown | 5 | 23% |
Attention Score in Context
This research output has an Altmetric Attention Score of 3. 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 October 2016.
All research outputs
#14,256,694
of 25,374,917 outputs
Outputs from Behavior Research Methods
#1,262
of 2,525 outputs
Outputs of similar age
#167,606
of 329,224 outputs
Outputs of similar age from Behavior Research Methods
#11
of 39 outputs
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