The Canto-Lexicon Project is a recent megastudy including lexical decision and naming data from native Cantonese speakers for 4376 most common traditional Chinese characters in Hong Kong. In addition to psycholinguistic measures from the Hong Kong Corpus of Chinese News-Paper (Leung & Lau, 2010), we collected new ratings of imageability, age of acquisition (AoA), concreteness, and familiarity of each character from twenty undergraduate raters. To gain a clearer view of the relationships between these inter-correlated variables among 3126 semantic-phonetic compound characters, we ran a principal component analysis. The variables loaded onto six main components with eigenvalues over 1, which together accounted for 84% of total variance. Component 1 consisted of character frequency, familiarity, and AoA. Component 2 consisted of phonetic consistency and phonetic radical combinability. Component 3 had loadings of concreteness, imageability, and semantic radical transparency. Component 4 consisted of orthographic neighborhood size and semantic radical combinability. Component 5 had loadings of perimetric complexity (i.e., number of pixels) and number of strokes. Component 6 consisted of number of homophones only. On-going work will provide additional calculations of semantic radical consistency, phonological neighborhood, contextual diversity, and other measures. Final results will contribute to deeper and broader understanding of the nature of Chinese characters, and provide interesting comparisons to global Chinese (simplified characters in mainland China and Singapore, or traditional characters in Taiwan). This database will be made available for online access, and could be a useful reference for researchers seeking to select experimental stimuli or clinical materials. Copyright © 2020 ARWA.
|Publication status||Published - Sep 2020|
CitationYum, Y. N., Su, I.-F., & Lau, D. K.-Y. (2020, September). Properties of single Chinese characters in Hong Kong from the Canto-Lexicon Project [Zoom]. Poster presented at the 4th Annual Conference for the Association for Reading and Writing in Asia (ARWA 2020), Beijing, China.
- Character database
- Psycholinguistic properties