The Large-Scale Structure of Semantic Networks: Statistical Analyses and a Model of Semantic Growth

@article{Steyvers2005TheLS,
  title={The Large-Scale Structure of Semantic Networks: Statistical Analyses and a Model of Semantic Growth},
  author={Mark Steyvers and Joshua B. Tenenbaum},
  journal={Cognitive science},
  year={2005},
  volume={29 1},
  pages={
          41-78
        }
}
We present statistical analyses of the large-scale structure of 3 types of semantic networks: word associations, WordNet, and Roget's Thesaurus. We show that they have a small-world structure, characterized by sparse connectivity, short average path lengths between words, and strong local clustering. In addition, the distributions of the number of connections follow power laws that indicate a scale-free pattern of connectivity, with most nodes having relatively few connections joined together… 
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