title: Mapping the structure of semantic memory.
abstract: Aggregating 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.
authors.affiliation: Max Planck Institute for Human Development, Center for Adaptive Behavior and Cognition, Berlin, Germany. morais@mpib-berlin.mpg.de
authors.forename: Ana Sofia
authors.initials: AS
authors.lastname: Morais
authors.forename: Henrik
authors.initials: H
authors.lastname: Olsson
authors.forename: Lael J
authors.initials: LJ
authors.lastname: Schooler
mesh_terms: D000328:Adult; D001245:Association Learning; D016000:Cluster Analysis; D003463:Cues; D005260:Female; D006801:Humans; D008297:Male; D011939:Mental Recall; D015233:Models, Statistical; D016571:Neural Networks, Computer; D012660:Semantics; D014706:Verbal Learning; D055815:Young Adult