期刊
JOURNAL OF DOCUMENTATION
卷 74, 期 1, 页码 99-118出版社
EMERALD GROUP PUBLISHING LTD
DOI: 10.1108/JD-04-2017-0057
关键词
Bibliometrics; Interdisciplinary studies; Machine learning; Chinese LIS; Citation preference; Knowledge import
资金
- National Natural Science Foundation of China [91546124]
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 paper fills the research gap in analyzing citations to WOD from Chinese LIS articles and their impacts on LIS, and recommends that Chinese LIS should emphasize on knowledge both on technology and people as well as knowledge from the practice community, cooperate with partners from other fields, thus to produce knowledge meeting the demands from library and information practice as well as users.
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