<abstract xmlns="http://www.w3.org/1999/xhtml"><sec><h3>Purpose</h3><p>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.</p></sec><sec><h3>Design/methodology/approach</h3><p>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.</p></sec><sec><h3>Findings</h3><p>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.</p></sec><sec><h3>Research limitations</h3><p>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.</p></sec><sec><h3>Practical implications</h3><p>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.</p></sec><sec><h3>Originality</h3><p>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.</p></sec></abstract>

PurposeResearch 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/approachIn 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.FindingsFor 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 limitationsThis 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 implicationsThis 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.OriginalityThe 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.

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

National Science Library, Chinese Academy of Sciences

University of Chinese Academy of Sciences

Journal of Data and Information Science

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

PurposeResearch dynamics have long been a research interest. It is a macro perspective tool for discovering temporal research trends of a certain discipline or...

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

Article Category: Research Paper

Online veröffentlicht: 28. Juli 2020

Seitenbereich: 19 - 34

Eingereicht: 08. Feb. 2020

Akzeptiert: 11. Juni 2020

DOI: https://doi.org/10.2478/jdis-2020-0034

Schlüsselwörter
Research dynamics, Forward chaining, Topic model, Scientific influence, Citations content analysis

© 2020 Xiaoli Chen et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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

Article Category: Research Paper

Online veröffentlicht: 28. Juli 2020

Seitenbereich: 19 - 34

Eingereicht: 08. Feb. 2020

Akzeptiert: 11. Juni 2020

DOI: https://doi.org/10.2478/jdis-2020-0034

SchlüsselwörterResearch dynamics, Forward chaining, Topic model, Scientific influence, Citations content analysis

© 2020 Xiaoli Chen et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Schlüsselwörter
Research dynamics, Forward chaining, Topic model, Scientific influence, Citations content analysis