Researchers made a breakthrough in understanding the universality of emotions across languages by using colexification analysis, a method of studying word associations. Their study identifies four central emotion-related concepts - "GOOD," "WANT," "BAD," and "LOVE" - as having the highest number of associations with other emotional words in multiple languages. This finding aligns with traditional semantic methods and natural semantic metalanguage (NSM), reinforcing the universality of these emotions.