Developing a Psychometric Tool to Measure the Emotional Impact of Visual Content
Name
cucu-thcucu-meng-bcs-2024-thesis.pdf
Description
Thesis PDF
Size
4.7 MB
Format
Adobe PDF
Checksum (MD5)
37eb02518c9141b32d741706a1ab0e31
Author(s)
Cucu, Theodor
Advisor(s)
DiCarlo, James J.
Date Issued
May 2024
Publisher
Massachusetts Institute of Technology
Abstract
This thesis investigates the human valence response to sequences of visual images. We f irst use crowd-sourcing and a novel nine-point psychometric scale to estimate human valence responses to individual images from the OASIS image set with high reliability (split-half Spearman rank-correlation ρ = 0.95). In a separate group of human participants, we then estimate valence responses following short, random sequences of those images (of length ≤ 10). Our key finding is that these sequence-contingent valence responses can be closely predicted by a simple linear combination of the estimated human valence responses to individual images (held-out ρ = 0.94). The combination weights are largest for the final image in the sequence; intuitively, this means the final image by itself can make predictions with high goodness-of-fit (ρ = 0.87). In summary, this research shows new evidence for a simple relationship between valence responses to individual images and valence responses to image sequences, with implications for future studies and practical applications in psychological assessment and beyond.
MIT Department
Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences
Terms of Use
Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)
Copyright retained by author(s)
Persistent DSpace Link
