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A Micro Perspective of Research Dynamics Through “Citations of Citations” Topic Analysis

机译：通过“引文引文”主题分析研究动态的微观视角

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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.
机译：目的研究动态长期以来一直是研究兴趣。它是一种宏观透视工具，用于发现某个学科或主题的时间研究趋势。然而，研究动态的微观视角，关于单一的研究人员或在他们的引文和“引文”（前瞻性链接）方面有高度引用的论文仍未开发。设计/方法/方法在本文中，我们使用跨收集主题模型来揭示主题失踪主题继承的研究动态，以及每代前进链接的主题创新。对高度引用的工作的调查结果，间接引用存在科学影响。主题建模可以揭示这种影响在前进链中的影响以及其影响力。研究限制本文仅在借用或间接引用中使用或间接引用的相关单词或短语时，才能衡量科学影响和间接科学影响。在这项研究中可以忽略释义或语义类似的概念。实际含义本文通过对前进链接分析，在间接引用中存在科学影响。这可以作为如何充分评估研究影响的灵感。原创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，我们使用跨收集主题模型模型失踪。其次，我们探讨了通过“引文的引用”内容分析的研究影响的长度和特征。最后，我们分析了人工智能研究员Geoffrey Hinton的出版物的研究动态以及前进链接的主题动态。

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