Semantic Acceptability of Second Language Noun-noun Compounds and its Correlates with Linguistic Profiles
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In psycholinguistics literature, a main divergence on noun-noun compounds such as orange juice is how the combinations of two nouns are mentally represented: full-listing models, full-paring models, and dual-route models. This study aims to address this representational issue by examining second language learners' offline semantic acceptability data while considering linguistic profiles of compounds (i.e., frequencies and the number senses of each constituents). L1 group and L2 group of an advanced level of English proficiency were asked to evaluate the semantic acceptability of 120 noun-noun compounds (60 well-formed and 60 ill-formed) on a 6-point scale. A multiple regression analysis revealed that the semantic acceptability by L1 group was positively correlated with the frequencies of compounds as a whole, which is in support of full-listing models. In contrast, a comparable statistical method for L2 group found that the semantic acceptability by L1 group was positively associated with the frequencies of compounds as a whole and are inversely with the number of senses of each constituent; and thus, the L2 data seem to lend a support for dual-route models.
Abstract
In psycholinguistics literature, a main divergence on noun-noun compounds such as orange juice is how the combinations of two nouns are mentally represented: full-listing models, full-paring models, and dual-route models. This study aims to address this representational issue by examining second language learners' offline semantic acceptability data while considering linguistic profiles of compounds (i.e., frequencies and the number senses of each constituents). L1 group and L2 group of an advanced level of English proficiency were asked to evaluate the semantic acceptability of 120 noun-noun compounds (60 well-formed and 60 ill-formed) on a 6-point scale. A multiple regression analysis revealed that the semantic acceptability by L1 group was positively correlated with the frequencies of compounds as a whole, which is in support of full-listing models. In contrast, a comparable statistical method for L2 group found that the semantic acceptability by L1 group was positively associated with the frequencies of compounds as a whole and are inversely with the number of senses of each constituent; and thus, the L2 data seem to lend a support for dual-route models.
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