Extrapolating continuous color emotions through deep learning

TL;DR

This paper employs deep learning to extrapolate emotional associations with colors from an experimental dataset, revealing gender and age-related trends and analyzing color-emotion relationships.

Contribution

It introduces a neural network-based method for predicting color-emotion associations and provides a mathematical analysis of the results, highlighting demographic differences and color confusion patterns.

Findings

Males associate darker colors with emotions

Females associate brighter colors with emotions

Older people tend to associate lighter colors with emotions

Abstract

By means of an experimental dataset, we use deep learning to implement an RGB extrapolation of emotions associated to color, and do a mathematical study of the results obtained through this neural network. In particular, we see that males typically associate a given emotion with darker colors while females with brighter colors. A similar trend was observed with older people and associations to lighter colors. Moreover, through our classification matrix, we identify which colors have weak associations to emotions and which colors are typically confused with other colors.