CLAD: A corpus-derived Chinese Lexical Association Database

Shu Yen Lin, Hsueh Chih Chen, Tao Hsing Chang, Wei En Lee, Yao Ting Sung

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

The application of word associations has become increasingly widespread. However, the association norms produced by traditional free association tests tend not to exceed 10,000 stimulus words, making the number of associated words too small to be representative of the overall language. In this study we used text corpora totaling over 400 million Chinese words, along with a multitude of association measures, to automatically construct a Chinese Lexical Association Database (CLAD) comprising the lexical association of over 80,000 words. Comparison of the CLAD with a database of traditional Chinese word association norms shows that word associations extracted from large text corpora are similar in strength to those elicited from free association tests but contain a much greater number of associative word pairs. Additionally, the relatively small numbers of participants involved in the creation of traditional norms result in relatively coarse scales of association measurement, whereas the differentiation of association strengths is greatly enhanced in the CLAD. The CLAD provides researchers with a great supplement to traditional word association norms. A query website at www.chinesereadability.net/LexicalAssociation/CLAD/ affords access to the database.

Original languageEnglish
Pages (from-to)2310-2336
Number of pages27
JournalBehavior Research Methods
Volume51
Issue number5
DOIs
Publication statusPublished - 2019 Oct 1

Keywords

  • Association measures
  • Chinese text corpora
  • Corpus-based
  • Corpus-derived
  • Lexical association
  • Word association
  • Word co-occurrence

ASJC Scopus subject areas

  • Experimental and Cognitive Psychology
  • Developmental and Educational Psychology
  • Arts and Humanities (miscellaneous)
  • Psychology (miscellaneous)
  • Psychology(all)

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