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Compositional processing in the recognition of Chinese compounds: Behavioural and computational studies
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Description: We examined whether the ease of combining constituent meanings into a compound influences compound word processing. To this end, we built a compositional distributed semantic model, the CAOSS model (Marelli et al., 2017, Cognition), to capture this semantic composition process. Four folders are established for this study: 1. Python script for CAOSS: The script by which we built the Chinese CAOSS model is provided. 2. Raw data: Three behavioural measures along with the variables of interest are provided. 3. R code for data analysis: The R script used to analyse the data is provided. 4. Supplementary Materials: Enclosed are results for five additional analyses that were not reported in the manuscript.
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