Structural Differences in the Semantic Networks of Simulated Word Learners

A learner’s semantic network represents the learner’s knowl-edge of words/concepts and the relations among them. The structure of this network is significant as it might reveal aspects of the developmental process that leads to the network. In this work, we use computational modeling to examine the struc-ture of semantic networks of different simulated word learn-ers. We find that the learned semantic knowledge of a learner that simulates a normally-developing child reflects the struc-tural properties found in adult semantic networks of words. In contrast, the network of a late-talking learner — one that sim-ulates a child with a marked delay in vocabulary acquisition — does not exhibit these properties. We discuss the implica-tions of this result for understanding the process of vocabulary acquisition and delay