Art and language hold similar places in human cognition. Every second our senses take in an overwhelming amount of information, and turn it into a format we can remember, recreate and share with others. Through art and language we can convey complexity with minimal expression.

Hieroglyphs. Photo by Jeremy Zero on Unsplash

We also abstract our language in order to describe concepts that encompass more and more elements (e.g. emotion + icon = emoticon), just like we create abstract art to represent multiple senses in a specific domain.

Abstract Art. Photo by lucia on Unsplash

Interpreting art and understanding language are both highly context-dependent, and while both have their basis on sharing what we know, we can also complicate them to make their communicative properties to be more exclusive.

Such dynamic qualities of art and language fascinate many modern scientists. Truly understanding how language works in human brains and recreating such processes through machines is one of the most highly investigated fields of study.

Standing on the middle ground between cognitive science, art and design, and data science, I am curious to learn how art and language connect, what are the common processes underlying their complexities (especially how we abstract), and when do their mechanisms diverge. I hope to log and share my process of research here as a series of posts as well as to share the technical steps I took to help those on the similar path and interest. As a first step, I will discuss the process of preprocessing art description data in Python.

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