Abstract Purpose Research dynamics have long been a research interest. It is a macro perspective tool for discovering temporal research trends of a certain discipline or subject. A micro perspective of research dynamics, however, concerning a single researcher or a highly cited paper in terms of their citations and “citations of citations” (forward chaining) remains unexplored. Design/methodology/approach In this paper, we use a cross-collection topic model to reveal the research dynamics of topic disappearance topic inheritance, and topic innovation in each generation of forward chaining. Findings For highly cited work, scientific influence exists in indirect citations. Topic modeling can reveal how long this influence exists in forward chaining, as well as its influence. Research limitations This paper measures scientific influence and indirect scientific influence only if the relevant words or phrases are borrowed or used in direct or indirect citations. Paraphrasing or semantically similar concept may be neglected in this research. Practical implications This paper demonstrates that a scientific influence exists in indirect citations through its analysis of forward chaining. This can serve as an inspiration on how to adequately evaluate research influence. Originality The main contributions of this paper are the following three aspects. First, besides research dynamics of topic inheritance and topic innovation, we model topic disappearance by using a cross-collection topic model. Second, we explore the length and character of the research impact through “citations of citations” content analysis. Finally, we analyze the research dynamics of artificial intelligence researcher Geoffrey Hinton's publications and the topic dynamics of forward chaining.

中文翻译：

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通过“引文”主题分析研究动态的微观视角

摘要目的研究动态一直是研究的热点。它是用于发现特定学科或学科的时间研究趋势的宏观视角工具。然而，关于单个作者或被高度引用的论文在其引用和“引用被引用”（正向链接）方面的研究动态的微观观点仍未得到探索。设计/方法/方法在本文中，我们使用交叉收集主题模型来揭示主题消失的主题继承和每一代正向链接中的主题创新的研究动态。调查结果对于高被引作品，间接引文中存在科学影响。主题建模可以揭示此影响在前向链接中存在多长时间以及其影响。研究局限性本文仅在借用或使用直接或间接引用相关单词或短语的情况下，才评估科学影响力和间接科学影响力。释义或语义相似的概念在本研究中可能被忽略。实际意义本文通过对前向链接的分析表明，间接引用中存在科学影响。这可以为如何充分评估研究影响力提供启发。创新性本文的主要贡献是以下三个方面。首先，除了主题继承和主题创新的研究动态之外，我们还使用交叉收集主题模型对主题消失进行建模。其次，我们通过“引文引用”内容分析来探索研究影响的长度和特征。最后，