↓ Skip to main content

Use-inspired basic research on individual differences in face identification: implications for criminal investigation and security

Overview of attention for article published in Cognitive Research: Principles and Implications, June 2018
Altmetric Badge

About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (75th percentile)

Mentioned by

blogs
1 blog
twitter
1 X user

Citations

dimensions_citation
48 Dimensions

Readers on

mendeley
79 Mendeley
Title
Use-inspired basic research on individual differences in face identification: implications for criminal investigation and security
Published in
Cognitive Research: Principles and Implications, June 2018
DOI 10.1186/s41235-018-0115-6
Pubmed ID
Authors

Karen Lander, Vicki Bruce, Markus Bindemann

Abstract

This journal is dedicated to "use-inspired basic research" where a problem in the world shapes the hypotheses for study in the laboratory. This review considers the role of individual variation in face identification and the challenges and opportunities this presents in security and criminal investigations. We show how theoretical work conducted on individual variation in face identification has, in part, been stimulated by situations presented in the real world. In turn, we review the contribution of theoretical work on individual variation in face processing and how this may help shape the practical identification of faces in applied situations. We consider two cases in detail. The first case is that of security officers; gatekeepers who use facial ID to grant entry or deny access. One applied example, where much research has been conducted, is passport control officers who are asked to match a person in front of them to a photograph shown on their ID. What happens if they are poor at making such face matching decisions and can they be trained to improve their performance? Second, we outline the case of "super-recognisers", people who are excellent at face recognition. Here it is interesting to consider whether these individuals can be strategically allocated to security and criminal roles, to maximise the identification of suspects. We conclude that individual differences are one of the largest documented sources of error in face matching and face recognition but more work is needed to account for these differences within theoretical models of face processing.

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user 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 79 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 79 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 14 18%
Student > Master 13 16%
Researcher 6 8%
Student > Bachelor 6 8%
Professor 3 4%
Other 13 16%
Unknown 24 30%
Readers by discipline Count As %
Psychology 34 43%
Neuroscience 4 5%
Social Sciences 4 5%
Medicine and Dentistry 3 4%
Computer Science 2 3%
Other 7 9%
Unknown 25 32%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 8. 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 05 September 2018.
All research outputs
#4,137,356
of 23,092,602 outputs
Outputs from Cognitive Research: Principles and Implications
#136
of 324 outputs
Outputs of similar age
#80,264
of 329,163 outputs
Outputs of similar age from Cognitive Research: Principles and Implications
#10
of 14 outputs
Altmetric has tracked 23,092,602 research outputs across all sources so far. Compared to these this one has done well and is in the 81st percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 324 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 43.6. 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 329,163 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 75% of its contemporaries.
We're also able to compare this research output to 14 others from the same source and published within six weeks on either side of this one. This one is in the 21st percentile – i.e., 21% of its contemporaries scored the same or lower than it.