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. The analysis of three datasets of
English language-learners' texts 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.

文本长度对词汇多样性的估计产生了一个世纪以来科学界的关注，虽然已提出许多指标和进行了许多研究来评估它们，但问题仍然存在。本方法论综述不仅对语言学习研究中最常用的指标进行了批判性分析，而且对于长度问题本身以及评估所提出解决方案的方法也进行了分析。对三个英语学习者文本数据集的分析表明，通过使用概率或算法方法将所有文本缩短到相同长度的指标解决了长度依赖性的问题；然而，所有这些指标都未解决第二个问题，即敏感性的参数决定缩短文本的长度。论文最后给出了优化词汇多样性分析的建议。