Quick summary:
- What I did:
- co-developed a scientific framework and Python package for analyzing the role of color in semantic meaning
- Things I learnt:
- how to build a Python package catered to the dynamic needs of a research team
- many fascinating ideas from cognitive science and color theory
- When was this?
- May 2019 through December 2019
I was fortunate to be part of a multidisciplinary, dynamic, and very skilled cohort at the Santa Fe Institute’s Complex Systems Summer School, 2019 (CSSS19).
Over discussions on the dependence of art of its observer, on an objective framework for judging art, on the nature of meaning and cognition, an idea was born - to attempt to trace color (broadly, visual signal) as a root of semantic meaning.
In our attempt to formalize the analysis, we dipped into color theory, cognitive theory, machine learning, and information theory.
The result was compsyn - a Python package that offers a novel method to explore the relationship between color and the semantic meaning of concepts.
The image below used our get_composite_image() method to generate a ‘colorgram’ of pictures of the entire CSSS19 cohort.
We now have a quantitative framework with which we can analyze digital images in a perceptually uniform colorspace and measure the statistical relationships between color and cognition.
pip install compsyn to try it yourself.