Comparar métodos
Examine os métodos selecionados lado a lado; as linhas que diferem ficam destacadas.
| Measure of Textual Lexical Diversity (MTLD)× | vocd-D (D Measure)× | |
|---|---|---|
| Área | Linguística | Linguística |
| Família | Process / pipeline | Process / pipeline |
| Ano de origem≠ | 2005 | 2004 |
| Autor original≠ | Philip M. McCarthy | David Malvern & Brian Richards |
| Tipo | Length-robust index of lexical diversity | Length-robust index of lexical diversity |
| Fonte seminal≠ | McCarthy, P. M., & Jarvis, S. (2010). MTLD, vocd-D, and HD-D: A validation study of sophisticated approaches to lexical diversity assessment. Behavior Research Methods, 42(2), 381–392. DOI ↗ | Malvern, D., Richards, B., Chipere, N., & Durán, P. (2004). Lexical Diversity and Language Development: Quantification and Assessment. Palgrave Macmillan. ISBN: 9781403902313 |
| Outros nomes≠ | MTLD, Measure of Textual Lexical Diversity, Sequential TTR Factor Measure | vocd-D, D Measure, vocd, HD-D |
| Relacionados | 4 | 4 |
| Resumo≠ | The Measure of Textual Lexical Diversity (MTLD) is a length-robust index of vocabulary richness introduced by Philip McCarthy in 2005 and validated by McCarthy and Jarvis in 2010. Rather than computing a single ratio over the whole text, MTLD reads the text word by word, tracking a running type-token ratio, and counts how many sequential word runs are needed before the ratio repeatedly falls to a criterion value of 0.720. The mean length of those runs, computed forward and backward and averaged, is the MTLD score — and in validation studies it was the one common index that did not vary systematically with text length. | vocd-D, also called the D measure, is a length-robust index of lexical diversity developed by David Malvern and Brian Richards. Instead of reporting a single type-token ratio, it characterizes how a text's TTR falls as sample size grows and fits that empirical curve to a one-parameter probabilistic model; the fitted parameter D is the diversity score, with higher D meaning richer vocabulary. HD-D, introduced by McCarthy and Jarvis, is the mathematically exact, sampling-free counterpart that computes the same underlying quantity directly from the hypergeometric distribution. |
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