Modeling bilingual word associations as connected monolingual networks

Word associations are a common tool in research on the mental lexicon. Studies report that bilinguals produce different word associations in their non-native language than monolinguals, and propose at least three mechanisms responsible for this difference: bilinguals may rely on their native associations (through translation), on collocational patterns, and on the phonological similarity between words. In this paper, we first test the differences between monolingual and bilingual responses, showing that these differences are consistent and significant. Second, we present a computational model of bilingual word associations, implemented as a semantic network paired with a retrieval mechanism. Our model predicts bilingual word associations better than monolingual baselines, and translation is the main mechanism explaining its success, while collocational and phonological associations do not improve the model.