The Development of Small-world Semantic Networks

Abstract

Cognitive processes rely on knowledge structures that can be represented by networks of interconnected concepts, i.e., semantic networks. We study the developmental dynamics of generic semantic-network models. We focus on two measures: (i) the characteristic path length between an arbitrary pair of concepts, and (ii) the clustering coefficient of groups of concepts. Short path lengths facilitate the dynamics of mental processes through spreading activation and a large clustering coefficient reflects the existence of structured representations. We analysed semantic-network models generated from behavioural data. We measure the characteristic path length and clustering coefficient at various stages of development. The results reveal semantic networks to be small-world networks, i.e., networks that combine short path lengths with high clustering. In addition, developing semantic networks are characterised by an increase in small-worldliness by maintaining a constant path length and clustering coefficient despite the increase in the number of concepts.