"It’s a Small World" of Signs: Semantic Network Structure in American Sign Language
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How is meaning structured in the mind? While decades of research on spoken languages have shown that words are organized into highly efficient “small-world” semantic networks, much less is known about how sign languages organize conceptual knowledge. We constructed large-scale semantic networks for American Sign Language (ASL) using a free sign association task, in which Deaf signers produced the first three signs that came to mind in response to a cue sign. Data were collected using a custom-built platform for sign language responses and annotation, resulting in over 100,000 cue–response pairs from 45 Deaf ASL signers. We analyzed the structure of the ASL semantic lexicon using network metrics such as clustering, average shortest path length, and modularity, and compared these properties to spoken English using data from the Small World of Words (SWOW) project. While both networks exhibited small-world characteristics, the ASL network was more modular and sparsely connected, indicating a more compartmentalized structure. Measures of semantic density and response diversity were positively related to lexical frequency, and phonological neighborhood density was also positively correlated with semantic density. These findings suggest that while signed and spoken languages share core organizing principles, language modality may shape how meaning is structured and accessed.