Developing a Psychometric Tool to Measure the Emotional Impact of Visual Content

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.

Name thesis:degree_name

Master

Department dc:contributor.department

Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2024

Author dc:creator

• Cucu, Theodor

Advisor dc:contributor.advisor

• DiCarlo, James J.

Statement dc:rights

• Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)
• Copyright retained by author(s)

Licence dc:rights.uri

• https://creativecommons.org/licenses/by-nc-nd/4.0/

Handle dc:identifier.uri

https://hdl.handle.net/1721.1/156957

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/156957