Adults with larger vocabularies produce more diverse word associations and organize their mental lexicon differently, according to a new study published in Applied Network Science. The research, led by C. Donnan Gravelle and Patricia J. Brooks, examined how word association networks differ as a function of vocabulary knowledge using two complementary methods: lexical metrics and latent space modeling.
The study involved 44 college students who completed a standardized assessment of receptive vocabulary knowledge and a repeated word association task. In the task, participants responded to cue words with the first word that came to mind, and they did so over three repetitions of the same list. This repeated design allowed the researchers to track how associations changed as the same cues were encountered again and again.
Each word association was coded for cue-response similarity using three measures: word embedding similarity, taxonomic similarity, and phonological similarity. The responses were also coded for word-level features, including concreteness, age of acquisition, and frequency.
The clearest behavioral difference emerged in the kinds of words participants produced. Those with higher vocabulary knowledge more often generated lower-frequency words with a later age of acquisition than participants with lower vocabulary knowledge. In other words, more knowledgeable speakers reached deeper into the lexicon, retrieving rarer words that are typically learned later in development.
Over the three list repetitions, a consistent pattern appeared across participants: cue-response similarity decreased, and responses more often involved lower-frequency words with a later age of acquisition.
To examine the structure of the associations at the network level, the researchers pooled word associations and constructed a latent space model. They then used lexical metrics and vocabulary knowledge, split into above-average and below-average groups, to predict edge weights, which represent word association strength between nodes in the network.
In this model, both word embedding similarity and word frequency predicted stronger edge weights. Over list repetitions, edge weights decreased, and the effect was larger in the below-average vocabulary network. This suggests that the weakening of associations across repeated cues was more pronounced among participants with smaller vocabularies.
The network structure itself also differed between groups. The above-average vocabulary network exhibited more clusters with shorter average distances between nodes, which the authors interpret as suggesting greater differentiation within the lexicon.
Taken together, the results indicate minimal differences in the cue-response similarities of word associations among adults varying in vocabulary knowledge, but more diverse word associations among those with above-average vocabularies. The authors suggest that growing one’s vocabulary over the lifespan may influence the organization of the mental lexicon by altering the proximities between neighboring words. Because the study involved a relatively small sample of 44 college students and a repeated association task, the findings describe associations in this population rather than establishing how vocabulary growth causes changes in lexical organization over time.
Subject of Research: How vocabulary knowledge relates to word association networks in adults
Article Title: How vocabulary knowledge influences word associations: applications of lexical metrics and latent space network models
Article References: Gravelle, C. D., & Brooks, P. J. (2026). How vocabulary knowledge influences word associations: applications of lexical metrics and latent space network models. Applied Network Science. https://doi.org/10.1007/s41109-026-00817-z
Image Credits: AI Generated
DOI: 10.1007/s41109-026-00817-z
Keywords: vocabulary knowledge, word associations, mental lexicon, latent space model, lexical networks, word frequency, age of acquisition, word embedding similarity, network clusters, college students, vocabulary, knowledge
News Source: Denise Maddox. (October 29, 2026). Vocabulary size shapes how adults link words in memory networks. Scienmag.
