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Depth analysis: What happens after papers stand on the giant's shoulder?

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Bibliographic Details
Title: Depth analysis: What happens after papers stand on the giant's shoulder?
Authors: Yoon, Jeeyoung1 (AUTHOR), Park, Ji-Hong1 (AUTHOR) jihongpark@yonsei.ac.kr
Source: Journal of Information Science. Dec2025, Vol. 51 Issue 6, p1409-1423. 15p.
Subject Terms: *Citation analysis, *Academic discourse, Neural computers, Epistemics, Research evaluation, Scholarly method, Contextual analysis
People: Newton, Isaac, 1642-1727
Abstract: Scholarly impact has been investigated with great enthusiasm. Scholarly activity has been understood to be accumulative, as Isaac Newton's famous quote – stand on the giant's shoulder – indicates, and citation reflects such act of knowledge accumulation and development. While citation count is indeed a robust indicator for academic assessment, given the accumulative and back-to-back nature of academic work, is limited since it does not take descending activities of a paper into consideration. This study suggests a novel approach, the Depth Analysis, which scrutinises descending papers – papers that stood on the giant's shoulder. Also, novel Depth-based paper assessment method and knowledge structure analysis approach are presented. To validate the method, a case study on conference papers in neural computing domain is conducted. The study result shows that Depth Analysis can capture diachronic scholarly impact and knowledge structure shift more thoroughly. [ABSTRACT FROM AUTHOR]
Database: Library, Information Science & Technology Abstracts
Description
Abstract:Scholarly impact has been investigated with great enthusiasm. Scholarly activity has been understood to be accumulative, as Isaac Newton's famous quote – stand on the giant's shoulder – indicates, and citation reflects such act of knowledge accumulation and development. While citation count is indeed a robust indicator for academic assessment, given the accumulative and back-to-back nature of academic work, is limited since it does not take descending activities of a paper into consideration. This study suggests a novel approach, the Depth Analysis, which scrutinises descending papers – papers that stood on the giant's shoulder. Also, novel Depth-based paper assessment method and knowledge structure analysis approach are presented. To validate the method, a case study on conference papers in neural computing domain is conducted. The study result shows that Depth Analysis can capture diachronic scholarly impact and knowledge structure shift more thoroughly. [ABSTRACT FROM AUTHOR]
ISSN:01655515
DOI:10.1177/01655515231171366