Extrapolating Continuous Color Emotions Through Deep Learning

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Date

2020

Authors

Ram, Vishaal
Schaposnik, Laura P.
Konstantinou, Nikos
Volkan, Eliz
Papadatou-Pastou, Marietta
Manav, Banu
Jonauskaite, Domicele
Mohr, Christine

Journal Title

Journal ISSN

Volume Title

Publisher

Amer Physical Soc

Open Access Color

GOLD

Green Open Access

Yes

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Publicly Funded

No
Impulse
Top 10%
Influence
Average
Popularity
Top 10%

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Journal Issue

Abstract

By means of an experimental dataset, we use deep learning to implement an RGB (red, green, and blue) 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 (type-m individuals) typically associate a given emotion with darker colors, while females (typef individuals) associate it 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.

Description

Keywords

Associations, Preferences, Age, FOS: Computer and information sciences, Computer and Information Sciences, Computer Science - Machine Learning, QC1-999, FOS: Physical sciences, Associations, Quantitative Biology - Quantitative Methods, Machine Learning (cs.LG), Age, colour; emotion; machine learning; neural network, Biological Physics, Preferences, Quantitative Methods, Physics - Biological Physics, Quantitative Methods (q-bio.QM), Physics, Deep learning, Neural network, Quantitative Biology, Biological Physics (physics.bio-ph), FOS: Biological sciences, Computer Science, Natural Sciences

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Fields of Science

0501 psychology and cognitive sciences, 05 social sciences

Citation

WoS Q

Q1

Scopus Q

Q1
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OpenCitations Citation Count
9

Source

Physical Review Research

Volume

2

Issue

3

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End Page

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Citations

Scopus : 15

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Mendeley Readers : 18

SCOPUS™ Citations

15

checked on Feb 03, 2026

Web of Science™ Citations

13

checked on Feb 03, 2026

Page Views

5

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Downloads

178

checked on Feb 03, 2026

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1.66493898

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