In a study at Kansas University conducted by Michael Vitevich, an attempt is made to map out the words of our vocabulary as they are represented in the human brain. What Vitevich hopes to learn from charting out our vocabularies in the brain is how victims of brain trauma regain their language skills, but this information can also be used to study many things including language development and processing. As it turns out, the idea of the “six degrees of separation” that was discussed in class shows up in these models. Most words are unusually close to one another, implying that the network must be extremely complex with many edges. The mappings themselves are done using the relation of words to one another based on their sound and meaning, as seen in the diagram below.
As mentioned in the article and seen from the diagram, there are several words that have many more edges than others. These words appear like the gatekeepers we have mentioned in class in the sense that removing, or “forgetting” one, will make it hard or impossible to connect or remember some words. For example, removing “peach” in the diagram will split the vocabulary of this person into two parts. Another related idea here is that of structural holes, which can be seen at the gatekeepers as well as other nodes that connect two large subsets of the graph. The structural holes can tell us a lot about the way humans think about things, and why certain words are clustered together. If researchers can learn where the key words, or gatekeepers, are in the word network, this can have major implications on helping children and brain trauma patients build up their vocabulary faster because these kind of words are essential for remembering many others. One can think of learning the word cat at a young age, and then immediately words like rat, fat, mat, etc. come along. Clearly, the network of words that our brains construct is a very complex system that relies on key words throughout, although finding the exact structure of the network still seems very fuzzy.
I wonder if there’s more research in word-word _meanings_ graphs (versus the way they sound as well). It makes that language is a sparse network on the structural level, but how sparse is it in our minds? (where Dog -> Cat -> Mouse, not just Dog -> Bog).