Goldenstein and Poschmann (hereafter GP, this volume, pp. 83–131) offer a novel approach, or combination of approaches, for tracking multiple layers of “meaning” in a collection of texts over time. The core theoretical argument is sound: Any given text conveys multiple layers of meaning simultaneously, the relationships across those layers may evolve dynamically over time in any given corpus, and different textanalytic tools capture different layers of meaning and should be able to characterize this co-evolution if used in combination. In fact, similar logic underlies recent developments at the cutting edge of natural language processing (NLP) research. There are, however, some pernicious measurement traps in the text-analytic techniques GP apply here, and in the absence of some important validation, we cannot be certain that they have captured the meaning they assert.

中文翻译：

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点评：社会科学文本分析中“意义”的含义

Goldenstein 和 Poschmann（以下简称 GP，本卷，第 83-131 页）提供了一种新颖的方法或方法的组合，用于随时间跟踪文本集合中的多层“含义”。核心理论论点是合理的：任何给定的文本同时传达多层含义，这些层之间的关系在任何给定语料库中可能随时间动态演变，不同的文本分析工具捕获不同的含义层，并且应该能够表征这种共同作用。如果结合使用进化。事实上，类似的逻辑是自然语言处理 (NLP) 研究前沿的最新发展的基础。然而，在此处应用的文本分析技术 GP 中存在一些有害的测量陷阱，并且在缺乏一些重要验证的情况下，