Word Co-occurrence in Child-directed Speech Predicts Children’s Free Word Associations (2020)

Abstract: The free association task has been very influential both in cognitive science and in computational linguistics. However, little research has been done to study how free associations develop in childhood. The current work focuses on the developmental hypothesis according to which free word associations emerge by mirroring the co-occurrence distribution of children’s linguistic environment. I trained a distributional semantic model on a large corpus of child language and I tested if it could predict children’s responses. The results largely supported the hypothesis: Co-occurrence-based similarity was a strong predictor of children’s associative behavior even controlling for other possible predictors such as phonological similarity, word frequency, and word length. I discuss the findings in the light of theories of conceptual development.

## introduction the mental lexicon is organized into a structure such that exposure to a given word, e.g. "cat", tends to activate semantically similar words such as "milk" or "dog" @xcite . in order to characterize this structure, researchers in cognitive science have often relied on the free association task where people are given a list of cue words and asked to provide the first words that come to mind. data from this task -especially the word association norms collected by @xcite -have proven successful in accounting for a variety of psycholinguistic phenomena @xcite . in addition, they have often been used as ground truth in evaluating the ability of nlp models to approximate human lexico-semantic organization @xcite @xcite . while adult word associations have been extensively studied, it is still poorly understood how these associations develop in childhood. this is a significant gap in the developmental literature: to the extent that word free associations help us understand conceptual organization, the study of how these associations develop can inform our theories of conceptual development @xcite . previous work has shown that adults' word associations can be predicted by patterns of cooccurrence in language use @xcite (but @xcite , that is, pairs of words that tend to appear as cue-response in the free association data are also those that co-occur frequently in the language people are exposed to. developmentally, thus, a plausible scenario is that word associations first originate in childhood by mirroring the co-occurrence distribution in the language children hear around them. previous research has shown that word co-occurrence can support linguistic and conceptual development (e.g., @xcite , here i investigate how co-occurrence in child-directed speech can predict children's free associations. the paper is organized as follows. first, i briefly present the data and methods. second, i 1) quantify the variability in children's associations compared to that of adults, 2) explore if, despite individual variability, co-occurrence probabilities predict word associations, and 3) test if co-occurrence similarity remains predictive when controlling for other factors such as phonological similarity, response frequency, and response length. finally, i discuss the results in the light of theories of early conceptual development. ## discussion despite the fact that free associations varied greatly from child to child, they were highly predicted by their co-occurrence-based similarity in the linguistic environment. this prediction remained strong even controlling for other factors that may influence children's responses such as phonological similarity, word frequency, and word length. i found an interesting developmental change that appears to take place between 3 and 8 years old and whereby children's responses reflect more and more the cooccurrence structure of their native language, while becoming less tied to the lower-level phonological similarity. that said, i also found a difference between older children and adults, suggesting this development continues well into late childhood. since free associations have been used to study conceptual organization, the current study contributes to the literature on conceptual development. a big challenge in this literature is to understand how taxonomic categories (e.g., animal vs. artifact) are formed by children despite the fact that members of such categories do not necessarily look similar (e.g., fish and bird). using free association data (the same i use here), @xcite showed that children's free associations become more paradigmatic/taxonomic in nature between 3 and 8 years old. researchers have suggested children can learn such abstract categories (at least partly) through the language they hear around them. in fact, cues from language can provide children with information beyond what they can obtain through observation alone @xcite @xcite . in particular, word co-occurrence in child-directed speech has been shown to be a reliable cue for several taxonomic categories @xcite . for example, though "fish" and "bird" do not look very similar, people talk about them in similar linguistic contexts, typically leading to a high co-occurrencebased similarity. the current study provides (correlational) evidence for this proposal by showing that, at the same time children's associations become more taxonomic (wojcik and kandhadai, 2019), they also become more tuned with the word co-occurrence distribution of their native language. i suggest that these are not totally independent developments, and more precisely, that the later could (at least partly) influence the former. if this were to be true, then we could possibly explain a major high-level episode in conceptual development based on a simple mechanism of tracking statistical co-occurrence in language (which we know children are highly skilled at, see @xcite . future investigations should go beyond the limitations of the current work. for example, here i predicted data from one set of children (free word association) with data about the experience of a completely different set (childes corpus). such a research approach has been used before (e.g., braginsky et al. 2019). it is cost-effective, allowing us to collect large data and average out differences between children and their input. however, this approach fundamentally limits the amount of variability we can capture in terms of how the input may influence uptake. one way to mitigate this limitation is through doing dense data analysis, correlating input and behavior for the same child (e.g., @xcite . another (complementary) approach is to explore if the phenomenon can be produced in controlled, albeit simplified, behavioral experiments (e.g., @xcite .