A Chinese Conceptual Semantic Feature Dataset (CCFD)

Behav Res Methods. 2021 Aug;53(4):1697-1709. doi: 10.3758/s13428-020-01525-x. Epub 2021 Feb 2.


Memory and language are important high-level cognitive functions of humans, and the study of conceptual representation of the human brain is a key approach to reveal the principles of cognition. However, this research is often constrained by the availability of stimulus materials. The research on concept representation often needs to be based on a standardized and large-scale database of conceptual semantic features. Although Western scholars have established a variety of English conceptual semantic feature datasets, there is still a lack of a comprehensive Chinese version. In the present study, a Chinese Conceptual semantic Feature Dataset (CCFD) was established with 1,410 concepts including their semantic features and the similarity between concepts. The concepts were grouped into 28 subordinate categories and seven superior categories artificially. The results showed that concepts within the same category were closer to each other, while concepts between categories were farther apart. The CCFD proposed in this study can provide stimulation materials and data support for related research fields. All the data and supplementary materials can be found at https://osf.io/ug5dt/ .

Keywords: Chinese; concept; dataset; semantic feature.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Brain
  • China
  • Humans
  • Language*
  • Semantics*