Comparing Word Frequency, Semantic Diversity, and Semantic Distinctiveness in Lexical Organization

Word frequency (WF) is a strong predictor of lexical behavior. However, much research has shown that measures of contextual and semantic diversity offer a better account of lexical behaviors than WF (Adelman et al., 2006; Jones et al., 2012). In contrast to these previous studies, Chapman and Martin (2022) recently demonstrated that WF seems to account for distinct and greater levels of variance than measures of contextual and semantic diversity across a variety of datatypes. However, there are two limitations to these findings. The first is that Chapman and Martin (2022) compared variables derived from different corpora, which makes any conclusion about the theoretical advantage of one metric over another confounded, as it could be the construction of one corpus that provides the advantage and not the underlying theoretical construct. Second, they did not consider recent developments in the semantic distinctiveness model (SDM; Johns, 2021a; Johns et al., 2020; Johns & Jones, 2022). The current paper addressed the second limitation. Consistent with Chapman and Martin (2022), our results showed that the earliest versions of the SDM were less predictive of lexical data relative to WF when derived from a different corpus. However, the later versions of the SDM accounted for substantially more unique variance than WF in lexical decision and naming data. The results suggest that context-based accounts provide a better explanation of lexical organization than repetition-based accounts.