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.
Highlights
The application of word associations has become increasingly widespread
One frequently used method to obtain word association data is to run free association tests in which a series of stimulus words are presented to respondents who must quickly reply with the word that first comes to mind upon reading or listening to the stimulus
The second possibility, which is demonstrative of our prediction for a good association database, is that association strengths of the normative word pairs are relatively high in the Chinese Lexical Association Database (CLAD), such that more than 10% of the normative responses are covered by the strongest 10% of the CLAD associates
Summary
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. Beyond using word association to examine individual cognitive structures and processes, psychologists have investigated the normality of word associations in order to capture the shared relational representations in lexical memory. Word association clearly has commercial and social value, and new applications are likely to continue to be put forward
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