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Studying the Effect of Globalization on Color Perception using Multilingual Online Recruitment and Large Language Models

Abstract

How does globalization impact the interaction between perception and language? Building on Berlin and Kay's foundational study of color naming, we recruited 2,280 online participants speaking 22 different languages. We show that color naming maps differ structurally across languages, even among internet users living in (mostly) industrial societies. We use Large Language Models (LLMs) to simulate the limits of globalization by reproducing the naming task with a highly multilingual artificial agent with access to global digital information. We show that while the LLM has access to all languages, it has language-specific color representations and the number of color terms is correlated across humans and LLMs. However, LLMs use more color terms than humans, indicating differences in the representation. These results suggest that globalization has not removed cultural distinctions in color concepts, as language continues to be a key factor in the diversity of perception and meaning.

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