Predicting Word Maturity from Frequency and Semantic Diversity: A Computational Study

Semantic word representation changes over different ages of childhood until it reaches its adult form. One method to formally model this change is the word maturity paradigm. This method uses a text sample for each age, including adult age, and transforms the samples into a semantic space by means of Latent Semantic Analysis. The representation of a word at every age is then compared with its adult representation via computational maturity indices. The present study used this paradigm to explore to the impact of word frequency and semantic diversity on maturation indices. To do this, word maturity indices were extracted from a Spanish incremental corpus and validated, using correlation scores with Age of Acquisition and Word Difficulty indices from previous studies. The results show that both frequency and semantic diversity predict word maturity but that the predictive capacity of frequency decreases as exposure to language increases. The latter result is discussed in terms of inductive processes suggested in previous studies