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| Keyness Analysis× | 搭配分析× | |
|---|---|---|
| 领域≠ | 语言学 | 文本挖掘 |
| 方法族 | Process / pipeline | Process / pipeline |
| 起源年份≠ | 1997 | 1990 |
| 提出者≠ | Mike Scott | Church & Hanks |
| 类型≠ | Corpus comparison of relative word frequencies | Statistical text-mining technique |
| 开创性文献≠ | Scott, M. (1997). PC analysis of key words — and key key words. System, 25(2), 233–245. DOI ↗ | Church, K.W. & Hanks, P. (1990). Word Association Norms, Mutual Information, and Lexicography. Computational Linguistics, 16(1), 22-29. link ↗ |
| 别名 | Keyword Analysis, Corpus Keyness, Keyness Statistics | word association, collocation extraction, Birliktelik Analizi (Collocation Analysis) |
| 相关 | 3 | 3 |
| 摘要≠ | Keyness analysis identifies the words that are characteristically frequent (or infrequent) in a target corpus relative to a reference corpus, using statistical tests to measure how unexpected each word's frequency is. Introduced by Mike Scott in 1997, it answers the question 'what is this text or collection distinctively about?' and is a central technique in corpus linguistics and corpus-assisted discourse analysis for surfacing the salient vocabulary of a genre, period, author, or social group. | Collocation analysis is a statistical text-mining technique that identifies word pairs or expressions that frequently occur together, using association measures rather than chance co-occurrence. Introduced in the lexicography work of Church and Hanks (1990), it is used for terminology extraction and language analysis, surfacing the multi-word units that carry meaning in a corpus. |
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