Characterizing the Large-Scale Structure of Multimodal Semantic Networks.

ABSTRACT: Humans organize semantic knowledge into complex networks that encode relations between concepts. The structure of those networks has broad implications for human cognitive processes, and for theories of semantic development. Evidence from large lexical networks such as those derived from word associations suggest that semantic networks are characterized by high sparsity and clustering while maintaining short average paths between concepts, a phenomenon known as a "small-world" network. It has also been argued that those networks are "scale-free," meaning that the number of connections (or degree) between concepts follows a power-law distribution, whereby most concepts have few connections, while a few have many. However, the scale-free property is still debated, and the extent to which the

SUBMITTER: Marjieh R 

PROVIDER: S-EPMC12550224 | biostudies-literature | 2025 Oct

REPOSITORIES: biostudies-literature