方法对比

	Collostructional Analysis	N-gram Analysis
领域	语言学	语言学
方法族	Process / pipeline	Process / pipeline
起源年份	2003	1999
提出者	Anatol Stefanowitsch & Stefan Th. Gries	Corpus linguists (Douglas Biber; lexical bundles tradition)
类型	Statistical association analysis of lexemes and grammatical constructions	Frequency analysis of contiguous word sequences
开创性文献	Stefanowitsch, A., & Gries, S. T. (2003). Collostructions: Investigating the interaction of words and constructions. International Journal of Corpus Linguistics, 8(2), 209–243.	Biber, D., Johansson, S., Leech, G., Conrad, S., & Finegan, E. (1999). Longman Grammar of Spoken and Written English. Longman. ISBN: 9780582237254
别名	Collexeme Analysis, Distinctive Collexeme Analysis, Co-varying Collexeme Analysis	Lexical Bundle Analysis, Cluster Analysis (corpus linguistics), Contiguous Sequence Analysis
相关	4	4
摘要	Collostructional analysis is a family of corpus-based methods, introduced by Anatol Stefanowitsch and Stefan Th. Gries in 2003, that quantify the mutual attraction or repulsion between specific words (lexemes) and the grammatical constructions they occur in. Rooted in construction grammar, it treats a construction — such as the ditransitive "V NP NP" or the "into-causative" — as a meaningful unit and asks which words are statistically drawn to it or kept from it. The core technique, simple collexeme analysis, cross-tabulates how often a lexeme appears in the construction against how often each appears elsewhere, and measures the strength of association, conventionally with a Fisher–Yates exact test. Two extensions handle near-synonymous constructions (distinctive collexeme analysis) and the joint behavior of two slots within one construction (co-varying collexeme analysis), making the method a rigorous quantitative window onto the lexis–grammar interface.	N-gram analysis is a corpus-linguistic technique that extracts and ranks every contiguous sequence of n words (or characters) in a corpus, exposing the recurrent multi-word units — two-word bigrams, three-word trigrams, and longer 'lexical bundles' — that make up a register or text type. By counting how often each sequence recurs, it reveals the prefabricated, formulaic backbone of language that single-word frequency lists cannot capture.