The preferences of Chinese LIS journal articles in citing works outside the discipline
| DOI | https://doi.org/10.1108/JD-04-2017-0057 |
| Pages | 99-118 |
| Date | 08 January 2018 |
| Published date | 08 January 2018 |
| Author | Chuanfu Chen,Qiao Li,Zhiqing Deng,Kuei Chiu,Ping Wang |
| Subject Matter | Library & information science,Records management & preservation,Document management,Classification & cataloguing,Information behaviour & retrieval,Collection building & management,Scholarly communications/publishing,Information & knowledge management,Information management & governance,Information management,Information & communications technology,Internet |
The preferences of Chinese LIS
journal articles in citing works
outside the discipline
Chuanfu Chen, Qiao Li and Zhiqing Deng
Department of Library Science, School of Information Management,
Wuhan University, Wuhan, China
Kuei Chiu
University Library, University of California, Riverside, California, USA, and
Ping Wang
Department of Archives and Government Information Management,
School of Information Management, Wuhan University, Wuhan, China
Abstract
Purpose –The purpose of this paper is to understand how Chinese library and information science (LIS)
journal articles cite works from outside the discipline (WOD) to identify the impact of knowledge import from
outside the discipline on LIS development.
Design/methodology/approach –This paper explores the Chinese LIS’preferences in citing WOD by
employing bibliometrics and machine learning techniques.
Findings –Chinese LIS citations to WOD account for 29.69 percent of all citations, and they rise over time.
Computer science, education and communication are the most frequently cited disciplines. Under the
categorization of Biglan model, Chinese LIS prefers to cite WOD from soft science, applied science or
nonlife science. In terms of community affiliation, the cited authors are mostly from the academic community,
but rarely from the practice community. Mass media has always been a citation source that is hard to ignore.
There is a strong interest of Chinese LIS in citing emerging topics.
Practical implications –This paper can be implemented in the reformulation of Chinese LIS knowledge
system, the promotion of interdisciplinary collaboration, the development of LIS library collection and faculty
advancement. It may also be used as a reference to develop strategies for the global LIS.
Originality/value –This paperfills the research gap in analyzingcitations to WOD from Chinese LIS articles
and their impacts on LIS, and recommends that Chinese LIS should emphasize on knowledge both on
technologyand people as well as knowledge from thepractice community, cooperatewith partners from other
fields, thusto produce knowledge meeting thedemands from library and informationpractice as well as users.
Keywords Bibliometrics, Interdisciplinary studies, Machine learning, Chinese LIS, Citation preference,
Knowledge import
Paper type Research paper
1. Introduction
The approach to knowledge production adopted by contemporary science community is
problem driven, blurring links between pure and applied and disciplinary borders and
leading to interdisciplinarity (Gibbons et al., 1994; Milojević, 2014). Interdisciplinary research is
increasingly significant and widespread (Szostak, 2008; Xu et al., 2016), generating innovation
(Cummings and Kiesler, 2005), complementing capabilities (Bidault and Hildebrand, 2014) and
addressing real-lifeproblems (Milojević,2014; Bornmann, 2017) by emphasizing and promoting
knowledge exchange and cross-disciplinary collaboration (Liu et al., 2011; Ma et al., 2014).
Library and information science (LIS) is commonly defined as an interdisciplinary field (Kärki,
1996; Saracevic, 1999; Prebor, 2010). With the economic reform and opening-up of China
Journal of Documentation
Vol. 74 No. 1, 2018
pp. 99-118
© Emerald PublishingLimited
0022-0418
DOI 10.1108/JD-04-2017-0057
Received 16 April 2017
Revised 28 July 2017
Accepted 3 August 2017
The current issue and full text archive of this journal is available on Emerald Insight at:
www.emeraldinsight.com/0022-0418.htm
The authors would like to acknowledge reviewers and all participants for their contribution to the
improvement of this study. This study is supported by a grant from the National Natural Science
Foundation of China under the agreement 91546124.
99
Preferences of
Chinese LIS
journal articles
in 1978, Chinese LIS has been growing at an accelerated pace (Wu and Yuan, 1994; Hu et al.,
2011). There have been more LIS articles listed in China National Knowledge Infrastructure
(CNKI) database (265,562) than in Library and Information Science Abstracts (195,472) during
the same period of 1998-2013. It is fair to say that, in the course of development, there is a
golden rule for all disciplines to have themselves as a solid base while strengthening their
communication with other disciplines, and there is no exception for Chinese LIS (Chen, 2012).
Since citation is an effective indicator of interdisciplinarity, knowledge exchange and
research collaboration across disciplines (Porter and Chubin, 1985; Linderman and
Chandrasekaran, 2010; Chang and Huang, 2012; Kodama et al., 2013), there are many studies
on LIS’preferences in citing works from outside the discipline (WOD) to explore its relationship
with other disciplines (Meyer and Spencer, 1996; Buttlar, 1999; Larivière et al., 2012; Chang and
Huang, 2012). While Chinese LIS is an indispensable part of global LIS with huge volume of
publications, little attention has been given to such an issue. The existing research works failed
to investigate it systematically, and most of those works are based on small-scale citation
analysis, thus leaving a research gap about the actual status. To address that gap, this paper
aims to offer insight into Chinese LIS knowledge import as well as its impacts on future
LIS development. Following questions will be answered:
RQ1. Which disciplines outside LIS do Chinese LIS researchers cite most frequently?
RQ2. What are the characteristics of cited WOD?
RQ3. What are the impacts of the cited disciplines on the development of Chinese LIS?
This paper starts with reviewing and s ynthesizing previous research works on
interdisciplinary knowledge import in LIS field by employing citation analysis. Then, it
studies knowledge import across disciplines by processing and analyzing citation data
collected and used specifically for this study. Next, it analyzes cited disciplines, citation
frequencies,their distribution and trend over time anddistribution of disciplines from outside
LIS by using subject categories in Biglan (1973a) model. The characteristics of cited
documents’authors, subjects, sourceperiodicals, language and currencywill also be analyzed.
In addition,it studies LIS citation to WOD by analyzing publicationtype, authors’community
affiliations, as well as topic and subject categories to investigate the influence of knowledge
from other disciplines. Finally, it will propose recommendations to reformulate knowledge
system, cooperate with partners from outside LIS and optimize knowledge import for the
promotion of interdisciplinary collaboration and the creation of demand-driven knowledge.
This paper contributes to enhancing and optimizing knowledge import and research
collaboration across disciplines, which have implications for the exploration of potentials for
innovationin knowledge production, the satisfaction of demandsfrom LIS practice and users,
the improvement of capabilities in both developing technologies and serving people and the
solution of real-life problems. Moreover, with the high rate of the growth of the data from
scientific publications (Larsen and Ins, 2010), statistical techniques from the previous
generation and cognitive ability of people areinadequate for the analysis of large amountsof
citation data (Glymour et al., 1996; Loh et al., 2003; Uramoto et al., 2004; Guruler et al., 2010).
Therefore, data mining becomes more important for discovering knowledge hidden in data
(Ho et al., 2003). Supervised machine learning classification technique and unsupervised
clustering technique are employed in thisstudy to analyze the authors’communityaffiliation
and subject of citationsautomatically, and have implications for creating innovative methods
in analyzing citation data, especially in large-scale citation analysis.
2. Literature review
Citation analysis is commonly used to study the interdisciplinarity of LIS and the influences
it received from outside the discipline (Meyer and Spencer, 1996; Buttlar, 1999; Tang, 2004).
100
JD
74,1
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