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Topic analysis of academic disciplines based on prolific and authoritative researchers

Chao Yang (Zhejiang University, Hangzhou, China)
Cui Huang (Zhejiang University, Hangzhou, China)
Jun Su (Tsinghua University, Beijing, China)
Shutao Wang (Zhejiang University, Hangzhou, China)

Library Hi Tech

ISSN: 0737-8831

Article publication date: 15 June 2021

Issue publication date: 30 November 2021

304

Abstract

Purpose

The paper aims to explore whether topic analysis (identification of the core contents, trends and topic distribution in the target field) can be performed using a more low-cost and easily applicable method that relies on a small dataset, and how we can obtain this small dataset based on the features of the publications.

Design/methodology/approach

The paper proposes a topic analysis method based on prolific and authoritative researchers (PARs). First, the authors identify PARs in a specific discipline by considering the number of publications and citations of authors. Based on the research publications of PARs (small dataset), the authors then construct a keyword co-occurrence network and perform a topic analysis. Finally, the authors compare the method with the traditional method.

Findings

The authors found that using a small dataset (only 6.47% of the complete dataset in our experiment) for topic analysis yields relatively high-quality and reliable results. The comparison analysis reveals that the proposed method is quite similar to the results of traditional large dataset analysis in terms of publication time distribution, research areas, core keywords and keyword network density.

Research limitations/implications

Expert opinions are needed in determining the parameters of PARs identification algorithm. The proposed method may neglect the publications of junior researchers and its biases should be discussed.

Practical implications

This paper gives a practical way on how to implement disciplinary analysis based on a small dataset, and how to identify this dataset by proposing a PARs-based topic analysis method. The proposed method presents a useful view of the data based on PARs that can produce results comparable to traditional method, and thus will improve the effectiveness and cost of interdisciplinary topic analysis.

Originality/value

This paper proposes a PARs-based topic analysis method and verifies that topic analysis can be performed using a small dataset.

Keywords

Acknowledgements

The authors acknowledge support from the Innovative Research Group Project of the National Natural Science Foundation of China (Grant No. 71721002), excellent Youth Project of the National Natural Science Foundation of China (Grant No. 71722002), the key project of Humanties and Social Sciences in Ministry of Education of China (Grant No. 18JZD056), MOE (Ministry of Education in China) Project of Humanities and Social Sciences (Grant No. 18YJC870022) and the General Program of National Natural Science Foundation of China (Grant No. 71673164). The findings and observations contained in this paper are those of the authors and do not necessarily reflect the views of the supporters.

Citation

Yang, C., Huang, C., Su, J. and Wang, S. (2021), "Topic analysis of academic disciplines based on prolific and authoritative researchers", Library Hi Tech, Vol. 39 No. 4, pp. 1043-1062. https://doi.org/10.1108/LHT-04-2020-0102

Publisher

:

Emerald Publishing Limited

Copyright © 2021, Emerald Publishing Limited

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