Measuring the interdisciplinary characteristics of Chinese research in library and information science based on knowledge elements
| Date | 29 May 2023 |
| Pages | 589-617 |
| DOI | https://doi.org/10.1108/AJIM-03-2022-0130 |
| Published date | 29 May 2023 |
| Author | Jinxiang Zeng,Shujin Cao,Yijin Chen,Pei Pan,Yafang Cai |
Measuring the interdisciplinary
characteristics of Chinese research
in library and information science
based on knowledge elements
Jinxiang Zeng
School of Economics and Management, South China Normal University,
Guangzhou, China
Shujin Cao
School of Information Management, Sun Yat-sen University, Shenzhen, China
Yijin Chen
School of Economics and Management, South China Normal University,
Guangzhou, China
Pei Pan
School of Information Management, Wuhan University, Wuhan, China, and
Yafang Cai
School of Economic and Management, South China Normal University,
Guangzhou, China
Abstract
Purpose –This study analyzed the interdisciplinary characteristics of Chinese research studies in library
and information science (LIS) measured by knowledge elements extracted through the Lexicon-
LSTM model.
Design/methodology/approach–Eight research themes w ere selected for experiment, with a large-scale
(N511,625) dataset of research papers from the China National Knowledge Infrastructure (CNKI)
database constructed. And it is complemented with multiple corpora. Knowledge elements were extracted
through a Lexicon-LSTM model. A subject knowledge graph is constructed to support the searching and
classification of knowledge elements. An interdisciplinary-weighted average citation index space was
constructed for measuring the interdisciplinary characteristics and contributions based on knowledge
elements.
Findings –The empirical research shows that the Lexicon-LSTM model has superiority in the accuracy of
extracting knowledge elements. In the field of LIS, the interdisciplinary diversity indicator showed an upward
trend from 2011 to 2021, while the disciplinary balance and difference indicators showed a downward trend.
The knowledge elements of theory and methodology could be used to detect and measure the interdisciplinary
characteristics and contributions.
Originality/value –The extraction of knowledge elements facilitates the discovery of semantic information
embedded in academic papers. The knowled ge elements were prove d feasible for measu ring the
interdisciplinary characteristics and exploring the changes in the time sequence, which helps for overview
the state of the arts and future development trend of the interdisciplinary of research theme in LIS.
Keywords Knowledge element, Interdisciplinary characteristics, Weighted average citations, Lexicon-LSTM,
Knowledge extraction, Interdisciplinary measurement
Paper type Research paper
Knowledge
extraction in
Chinese LIS
research
589
Grant sponsor: This study was funded by the Major Project of Key University-Based National Research
Institute of Humanities and Social Sciences of the Ministry of Education, China, Grant number
22JJD870004; Science and Technolog y Project of Guangdong Province, China, Gra nt number
2020A1010020032.
The current issue and full text archive of this journal is available on Emerald Insight at:
https://www.emerald.com/insight/2050-3806.htm
Received 15 March 2022
Revised 3 June 2022
9 September 2022
7 December 2022
20 February 2023
2 April 2023
Accepted 2 April 2023
Aslib Journal of Information
Management
Vol. 75 No. 3, 2023
pp. 589-617
© Emerald Publishing Limited
2050-3806
DOI 10.1108/AJIM-03-2022-0130
1. Introduction
Interdisciplinary scientific research cooperation has been a hot topic of academic research in
the new era. Interdisciplinary research has contributed to its development in the evolution of
knowledge (Piggott et al., 2019). Different methods have been used to measure issues across
disciplines. Through literature cross-referencing, it is found that management research is
more often cited from social science literature than other disciplines (Neeley, 1981). Through
contextual knowledge extraction, Parti and Szigeti (2021) found that the citation of
gamification techniques influences the dynamics of urban development research and the
revision of scientific research directions.
The development of scholarly disciplines partly depends on the contribution of external
factors (Vakkari et al., 2022). The external features include cooperation intensity, influence
and cooperative institutions. The internal features include keywords and citation content.
The knowledge element is considered as the smallest controllable component of explicit
knowledge (West et al., 2014). Knowledge elements are connected through certain semantics,
which can generate knowledge with added value and even new knowledge. And they provide
efficient support in scientific research innovation, scientific research direction selection and
knowledge evolution. Citation-based social network analysis methods (Han et al., 2015;Shi
and Wang, 2022) were used in most early research studies to measure interdisciplinary
variability based on explicit knowledge in references of papers.
While content analysis based on topic identification is more about measuring potential
knowledge and combining multi-dimensional information such as subject categories, chapter
information and specific terms, contents demonstrate contributions to knowledge systems more
directly than citations (Wang et al., 2022). The overlapping community algorithm was used to
identify the intersections and potential intersections between disciplines in the co-word network
(Li et al.,2013). Knowledge memes were introduced to quantify knowledge flow across disciplines
from the novelty of content (Mao et al.,2020). The final extracted knowledge elementscan better
reflect the knowledge flow between papers, but there are also problems such as difficult
extraction, complex topic division and the need to introduce too much subjective evaluation.
This study aims to measure interdisciplinary characteristics based on knowledge
elements extracted from academic papers in Chinese library and information science (LIS)
field. Specifically, the main research questions of this article are as follows:
RQ1. How to extract and classify the knowledge elements of Chinese academic literature
in LIS field?
RQ2. How to measure the proportion and changes of interdisciplinary and non-
interdisciplinary papers in the selected samples based on knowledge elements over time?
RQ3. How to evaluate the contribution of interdisciplinary on high-cited papers based on
knowledge elements?
2. Related work
Existing research has discussed knowledge elements-extraction from scientific literature and
measurement of interdisciplinary degrees based on literature content. Further subdivision of
content analysis methods based on knowledge element identification can be grouped into two
categories: academic term-based and citation sentence-based interdisciplinary measurement.
2.1 Knowledge elements and extraction process
Knowledge organization based on knowledge element has been developed significantly.
It was first proposed by Wen and Wen (2011), using the knowledge classification idea of
AJIM
75,3
590
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