Using cluster analysis to quantify systematicity in a face image sorting task
| dc.contributor.author | Campbell, Alison | |
| dc.contributor.supervisor | Tanaka, James William | |
| dc.date.accessioned | 2017-08-29T21:08:48Z | |
| dc.date.available | 2017-08-29T21:08:48Z | |
| dc.date.copyright | 2017 | en_US |
| dc.date.issued | 2017-08-29 | |
| dc.degree.department | Department of Psychology | |
| dc.degree.level | Master of Science M.Sc. | en_US |
| dc.description.abstract | Open sorting tasks that include multiple face images of the same person require participants to make identity judgments in order to group images of the same person. When participants are unfamiliar with the identity, natural variation in the images due to changes in lighting, expression, pose, and age lead participants to divide images of the same person into different “identity” piles. Although this task is being increasingly used in current research to assess unfamiliar face perception, no previous work has examined whether there is systematicity across participants in how identity groups are composed. A cluster analysis was performed using two variations of the original face sorting task. Results identify groups of images that tend to be grouped across participants and even across changes in task format. These findings suggest that participants responded to similar signals such as tolerable change and similarity across images when ascribing identity to unfamiliar faces. | en_US |
| dc.description.scholarlevel | Graduate | en_US |
| dc.identifier.uri | http://hdl.handle.net/1828/8493 | |
| dc.language | English | eng |
| dc.language.iso | en | en_US |
| dc.rights | Available to the World Wide Web | en_US |
| dc.subject | Cluster analysis | en_US |
| dc.subject | Face | en_US |
| dc.subject | Face perception | en_US |
| dc.subject | Image analysis | en_US |
| dc.title | Using cluster analysis to quantify systematicity in a face image sorting task | en_US |
| dc.type | Thesis | en_US |