Supporting data for “Words in Minds and Machines: A Computational Characterization of Chinese Mental Lexicon”

Supporting data for “Words in Minds and Machines: A Computational Characterization of Chinese Mental Lexicon” are made available on HKU DataHub. In this research project, I took advantage of distributional semantic models to address the central question of how we mentally represent lexical semantic information. With a special focus on Chinese, I investigated a number of research topics including (i) compound compositionality, (ii) lexical ambiguity, and (iii) the extrapolation of semantic rating norms (i.e., valence, arousal, and concreteness) that could reflect individual differences. As no human participants were recruited for the purpose of the series of studies, only data derived from computational models, as well as the codes to implement the computations are provided. Researchers can utilize the data and codes to replicate the results described in this thesis. For details of the supporting data, please refer to the README file.