The Atkins/Levin article on the electronic corpus of language made the point that now there is the possibility of an electronic corpus, it is almost harder to decide how to classify linguistic data. They did this by studying groups of near-synonyms, specifically the shake verbs of quake, quiver, shake, shiver, shudder, tremble, and vibrate. These verbs are used to explore what should be classified in the next corpus. What could help is the classification of morphemes in Haspel's chapter. Morphemes are the smallest meaningful constituents of a linguistic expression. The verb endings of each word are different and this could help in classifying the linguistic data.
This, to me, is so different from Slobin's studies on frog studies. Showing stories about frogs without words is hard to connect to classifying linguistic data. However, the research done by the study about how language is learned can be connected to classifying linguistic data. Maybe a way to classify linguistic data is though which verb endings are more easily learned, or which of the symptoms most easily come to mind when reading the story. When seeing a picture of a tree moving, is it shake, quiver, shiver, shudder, tremble, or vibrate which first comes to mind to the participants in a study? This can help with classifying the data on these verbs.
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