
AbstractAggregating snippets from the semantic memories of many individuals may not yield a good map of an individual’s semantic memory. The authors analyze the structure of semantic networks that they sampled from individuals through a new snowball sampling paradigm during approximately 6 weeks of 1‐hr daily sessions. The semantic networks of individuals have a small‐world structure with short distances between words and high clustering. The distribution of links follows a power law truncated by an exponential cutoff, meaning that most words are poorly connected and a minority of words has a high, although bounded, number of connections. Existing aggregate networks mirror the individual link distributions, and so they are not scale‐free, as has been previously assumed; still, there are properties of individual structure that the aggregate networks do not reflect. A simulation of the new sampling process suggests that it can uncover the true structure of an individual’s semantic memory.
Adult, Male, Models, Statistical, Association Learning, Verbal Learning, Semantics, Young Adult, Mental Recall, Cluster Analysis, Humans, Female, Neural Networks, Computer, Cues
Adult, Male, Models, Statistical, Association Learning, Verbal Learning, Semantics, Young Adult, Mental Recall, Cluster Analysis, Humans, Female, Neural Networks, Computer, Cues
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