The impact of text length on the estimation of lexical diversity has captured the attention of the scientific community for more than a century. Numerous indices have been proposed, and many studies have been conducted to evaluate them, but the problem remains. This methodological review provides a critical analysis not only of the most commonly used indices in language learning studies, but also of the length problem itself, as well as of the methodology for evaluating the proposed solutions. Analysis of three data sets of texts produced by English language learners revealed that indices that reduce all texts to the same length using a probabilistic or an algorithmic approach solve the length-dependency problem; however, all these indices failed to address the second problem, which is their sensitivity to the parameter that determines the length to which the texts are reduced. The paper concludes with recommendations for optimizing lexical diversity analysis.

中文翻译：

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测量文本中的词汇多样性：双重长度问题

一个多世纪以来，文本长度对词汇多样性估计的影响引起了科学界的关注。人们提出了许多指标，并进行了许多研究来评估它们，但问题仍然存在。这种方法论回顾不仅对语言学习研究中最常用的指标进行了批判性分析，而且还对长度问题本身以及评估所提出的解决方案的方法进行了批判性分析。对英语学习者生成的三个文本数据集的分析表明，使用概率或算法方法将所有文本减少到相同长度的索引解决了长度依赖性问题；然而，所有这些索引都未能解决第二个问题，即它们对决定文本长度缩减的参数的敏感性。本文最后提出了优化词汇多样性分析的建议。