Inventor bibliographic-patent-coupling analysis and inventor-patent-classification-coupling analysis: a comparative analysis based on NPE

Song Yanhui () and Lei Lixin
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Song Yanhui: Hangzhou Dianzi University
Lei Lixin: Hangzhou Dianzi University

Scientometrics, 2024, vol. 129, issue 2, No 2, 745-765

Abstract: Abstract The patent literature is an important scientific and technological literature, which integrates technical information, market information, and legal information. It is of great significance to expand the bibliometric methods to the measurement of patent literature. This paper takes 4624 NPE (Non Practicing Entities) patents as samples and establishes an inventor coupling network based on two types of feature items, patent literature and Derwent classification codes. We have explored the technical structure of NPE patents. Through centrality analysis, correlation analysis, factor analysis, and visualization analysis, the two coupling analysis methods of Inventor Bibliographic-Patent-Coupling (IBPCA) and Inventor Patent Classification-Coupling (IPPCA) are compared. It is found that inventor centrality analysis, frequency correlation analysis, and cosine similarity measurement all show that IBPCA is correlated with IPPCA; The core technical topics of NPE patents discovered by IBPCA and IPCCA are digital computers, digital telecommunication transmission, and data storage and transmission. However, the two methods differ in factor models fitting analysis and intellectual structure detection. The factor fitting analysis of IPPCA is better than that of IBCCA; IBPCA can detect more topics than IPCCA, and has more advantages in small-scale topic detection; IPCCA is more sensitive to traditional and more stable research topics. Therefore, The combination of the two methods for intellectual structure detection and analysis will be more effective, then more comprehensive and specific conclusions will be obtained.

Keywords: Inventor bibliographic-patent-coupling analysis; Inventor patent classification-coupling analysis; Patent analysis (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/s11192-023-04713-6

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