KeyWords Plus and Medical Subject Headings (MeSH) are widely used in bibliometric studies for topic mapping. The objective of this study is to compare the two description systems in documents about cannabis research to find the concordance between systems and establish whether there is neutrality in topic mapping. A total of 25,593 articles from 1970 to 2019 were drawn from Web of Science's Core Collection and Medline and analyzed. The tidytext library, Zipf's law, topic modeling tools, the contingency coefficient, Cramer's V, and Cohen's kappa were used. The results included 10,107 MeSH terms and 28,870 KeyWords Plus terms. The Zipf distribution of the terms was different for each system in terms of slope and specificity. The documents were classified into seven topics, and the MeSH system proved better at classification. The kappa coefficient between the two systems was 0.477 (for gamma ≥ 0.2); the topics related with human beings presented higher concordance. The use of KeyWords Plus for topic analyses in biomedical areas is not neutral, and this point needs to be taken into account in interpreting results.

KeyWords Plus 和医学主题词 (MeSH) 广泛用于主题映射的文献计量研究。本研究的目的是比较关于大麻研究的文件中的两种描述系统，以找到系统之间的一致性，并确定主题映射是否存在中立性。从 Web of Science 的 Core Collection 和 Medline 中抽取了 1970 年至 2019 年的 25,593 篇文章进行了分析。使用了 tidytext 库、Zipf 定律、主题建模工具、权变系数、Cramer's V 和 Cohen's kappa。结果包括 10,107 个 MeSH 术语和 28,870 个 KeyWords Plus 术语。就斜率和特异性而言，每个系统的项的 Zipf 分布是不同的。文档被分为七个主题，并且证明 MeSH 系统在分类​​方面更好。两个系统之间的 kappa 系数为 0.477（对于 gamma ≥ 0.2）；与人类相关的话题呈现出更高的一致性。使用KeyWords Plus进行生物医学领域的主题分析并不是中立的，在解释结果时需要考虑这一点。