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 6weeks 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.
Original language | English (US) |
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Pages (from-to) | 125-145 |
Number of pages | 21 |
Journal | Cognitive Science |
Volume | 37 |
Issue number | 1 |
DOIs | |
State | Published - 2013 |
Externally published | Yes |
Keywords
- Individual semantic networks
- Power laws
- Scale-free
- Small-worlds
- Snowball sampling
ASJC Scopus subject areas
- Experimental and Cognitive Psychology
- Cognitive Neuroscience
- Artificial Intelligence