Literature reviews summarize existing literature, uncover research gaps, and offer future research directions, thus aiding in theoretical and methodological development. Informetric research including bibliometric, scientometric, webometric, cybermetric, patentometric, and altmetric methods are becoming increasingly prevalent in conducting literature review studies. Looking at the common informetric literature review methods—citation, co‐citation, co‐author, bibliographic coupling, and content co‐occurrence analyses, this study aims to serve as a guide in using content co‐occurrence also known as co‐word analysis to conduct literature reviews. This study outlines a variety of informetric research methods and how they are utilized to conduct review and evidence‐based conceptual studies. In addition to the analyses, the study highlights different informetric software packages like Bibliometrix, Biblioshiny, Leximancer, NVivo, and CiteSpace including their comparison. The study further discusses contributions of algorithm‐based content analyses including offering taxonomies, definitions, classifications, typologies, comparisons, and theoretical development to constitute integrative literature reviews. Finally, this study offers step‐by‐step guidelines for conducting a review study using VOSviewer content co‐occurrence analysis while providing a systems view of informetric research in social science. The study also notes the emergence of generative artificial intelligence (AI) like Open AI's ChatGPT, Google's Bard, Elicit, Scite, Research Rabbit, and ChatPDF among others, and its potential in contributing to the literature review methods and, as such, being an interesting direction for future research.

中文翻译：

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如何进行文献计量内容分析：内容共现或共词文献综述的指南和贡献

文献综述总结了现有文献，发现研究空白，并提供未来的研究方向，从而有助于理论和方法的发展。信息计量研究，包括文献计量、科学计量、网络计量、网络计量、专利计量和替代计量方法，在文献综述研究中变得越来越普遍。着眼于常见的信息计量文献综述方法——引文、同被引、共同作者、书目耦合和内容共现分析，本研究旨在为内容共现（也称为共词分析）的使用提供指导进行文献综述。本研究概述了各种信息计量研究方法以及如何利用它们进行回顾和基于证据的概念研究。除了分析之外，该研究还重点介绍了不同的信息计量软件包，例如 Bibliometrix、Biblioshiny、Leximancer、NVivo 和 CiteSpace，包括它们的比较。该研究进一步讨论了基于算法的内容分析的贡献，包括提供分类法、定义、分类、类型、比较和理论发展以构成综合文献综述。最后，本研究提供了使用 VOSviewer 内容共现分析进行综述研究的分步指南，同时提供了社会科学信息计量研究的系统视图。该研究还指出了生成式人工智能 (AI) 的出现，例如 Open AI 的 ChatGPT、Google 的 Bard、Elicit、Scite、Research Rabbit 和 ChatPDF 等，以及它对文献综述方法做出贡献的潜力，因此成为一种未来研究的有趣方向。