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Exploring the relationship between team institutional composition and novelty in academic papers based on fine-grained knowledge entities

Ziling Chen (School of Economics and Management, Nanjing University of Science and Technology, Nanjing, China)
Chengzhi Zhang (School of Economics and Management, Nanjing University of Science and Technology, Nanjing, China)
Heng Zhang (School of Economics and Management, Nanjing University of Science and Technology, Nanjing, China)
Yi Zhao (School of Economics and Management, Nanjing University of Science and Technology, Nanjing, China)
Chen Yang (School of Economics and Management, Nanjing University of Science and Technology, Nanjing, China)
Yang Yang (School of Economics and Management, Nanjing University of Science and Technology, Nanjing, China)

The Electronic Library

ISSN: 0264-0473

Article publication date: 9 July 2024

Issue publication date: 31 October 2024

174

Abstract

Purpose

The composition of author teams is a significant factor affecting the novelty of academic papers. Existing research lacks studies focusing on institutional types and measures of novelty remained at a general level, making it difficult to analyse the types of novelty in papers and to provide a detailed explanation of novelty. This study aims to take the field of natural language processing (NLP) as an example to analyse the relationship between team institutional composition and the fine-grained novelty of academic papers.

Design/methodology/approach

Firstly, author teams are categorized into three types: academic institutions, industrial institutions and mixed academic and industrial institutions. Next, the authors extract four types of entities from the full paper: methods, data sets, tools and metric. The novelty of papers is evaluated using entity combination measurement methods. Additionally, pairwise combinations of different types of fine-grained entities are analysed to assess their contributions to novel papers.

Findings

The results of the study found that in the field of NLP, for industrial institutions, collaboration with academic institutions has a higher probability of producing novel papers. From the contribution rate of different types of fine-grained knowledge entities, the mixed academic and industrial institutions pay more attention to the novelty of the combination of method indicators, and the industrial institutions pay more attention to the novelty of the combination of method tools.

Originality/value

This paper explores the relationship between the team institutional composition and the novelty of academic papers and reveals the importance of cooperation between industry and academia through fine-grained novelty measurement, which provides key guidance for improving the quality of papers and promoting industry–university–research cooperation.

Keywords

Acknowledgements

This study is supported by the National Natural Science Foundation of China (Grant No. 72074113) and the Open Funding Project of Laboratory of IST IC-Springer Nature Joint Laboratory for Open Science (Grant No. ISN23012).

Citation

Chen, Z., Zhang, C., Zhang, H., Zhao, Y., Yang, C. and Yang, Y. (2024), "Exploring the relationship between team institutional composition and novelty in academic papers based on fine-grained knowledge entities", The Electronic Library, Vol. 42 No. 6, pp. 905-930. https://doi.org/10.1108/EL-03-2024-0070

Publisher

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Emerald Publishing Limited

Copyright © 2024, Emerald Publishing Limited

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