Determining the critical thresholds for co-word network based on the theory of percolation transition. A case study in Buddhist studies
| Published date | 11 December 2019 |
| Pages | 462-483 |
| DOI | https://doi.org/10.1108/JD-06-2019-0117 |
| Date | 11 December 2019 |
| Author | Muh-Chyun Tang,Weijen Teng,Miaohua Lin |
| 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 |
Determining the critical
thresholds for co-word
network based on the theory
of percolation transition
A case study in Buddhist studies
Muh-Chyun Tang
Department of Library and Information Science,
National Taiwan University, Taipei, Taiwan
Weijen Teng
Department of Buddhist Studies,
Dharma Drum Institute of Liberal Arts, Taipei, Taiwan, and
Miaohua Lin
Department of Library and Information Science,
National Taiwan University, Taipei, Taiwan
Abstract
Purpose –One of the chief purposes of bibliometric analysis is to reveal the intellectual structure of a
knowledge domain. Yet due to the magnitude and the heterogeneous nature of bibliometric networks, some
sorts of filtering procedures are often required to make the resulting network interpretable. A co-word
analysis of more than 135,000 scholarly publications on Buddhism was conducted to compare the intellectual
structure of Buddhist studies in three language communities, Chinese, English and Japanese, over two periods
(1957–1986 and 1987–2016). Six co-word similarity networks were created so social network analysis-based
community-detection algorithm can be identified to compare major research themes in different languages
and eras. The paper aims to discuss this issue.
Design/methodology/approach –A series of filtering procedures was performed to exclude less
discriminatory keywords and spurious relationships of a large, cross-language co-word network in Buddhist
studies. Chief among the filtering heuristics was a percolation-transition based method to determine the
similarity threshold that involves observing the relative decrease of nodes in the giant component with the
increasing similarity threshold.
Findings –It was found that the topical patterns in the Chinese and Japanese scholarship of Buddhism are
alike and observably distinct from that of the English scholarship. Furthermore, a far more drastic changes of
research themes were observed in the English literature relative to the Chinese and Japanese literature.
Originality/value –The filtering procedures were shown to greatly enhance the modularity values and
limited the number of modularity classes; thus, domain expert interpretation is feasible.
Keywords Co-word analysis, Buddhist studies, Critical thresholds
Paper type Research paper
Introduction
This paper reports a co-word domain analysis of the literature on Buddhism collected by the
Digital Library and Museum of Buddhist Studies (DLMBS) at National Taiwan University.
Established in 1995, DLMBS is among the most comprehensive online catalogs of Buddhist
research materials worldwide, and currently contains more than 400,000 records of books,
research papers, theses, and digitized Buddhist scriptures and artifacts in 45 languages.
A controlled vocabulary, which is in five languages, namely, Chinese, English, Japanese,
German and French, is used to help users search the DLMBS’s bibliographic database. The
collection’s comprehensiveness affords a rare opportunity to explore the evolution of
Journal of Documentation
Vol. 76 No. 2, 2020
pp. 462-483
© Emerald PublishingLimited
0022-0418
DOI 10.1108/JD-06-2019-0117
Received 18 June 2019
Revised 4 November 2019
Accepted 4 November 2019
The current issue and full text archive of this journal is available on Emerald Insight at:
www.emeraldinsight.com/0022-0418.htm
462
JD
76,2
Buddhist studies in different language communities and across different eras. By using the
co-occurrence data of author-assigned keywords in the literature collected from the DLMBS,
six co-word networks were generated in Chinese, English and Japanese, across two time
periods; thus, Buddhist studies in different language communities and time periods could
be compared.
Mapping knowledge domains in the humanities presents a special challenge, as it has
been argued that the characteristics of scholarly practices in the humanities do not lend
themselves well to the application of customary bibliometric methods (Chen et al., 2015; Fry,
2006; Hammarfelt, 2014; Nederhof, 2006). These include diverse publications channels, such
as monographs, books chapters and articles in research and nonacademic periodicals.
Disciplines within the humanities also tend to have a much stronger national or regional
focus, which makes their coverage less comprehensive in the English language–dominated
citation databases. Although co-word analysis has been widely used in the domains of
science and technology, co-word analysis for mapping knowledge domains in the
humanities has been applied in relatively few studies (Leydesdorff et al., 2011; Puschmann
and Bastos, 2015; Tang et al., 2017; Wang, 2018).
An advantage of co-word analysis in science and technology is that the subject
languages in these domains tend to be highly codified; therefore, a high degree of
consistency between concepts and terms warrants the resolution and interpretability of the
subspecialties. In contrast, the vocabularies in social sciences and humanities, in general, are
known to be less precise as they often found their way into common parlance. The esoteric
nature of Buddhist terminology circumvents the aforementioned problem of multivocality.
In a sense, it resembles the codified language found in science and technology. Furthermore,
from the methodological perspective, the co-word analysis also presents a viable alternative
to citation-based network analysis in the humanities, where the citation structure is much
sparser than in the various fields of science and technology.
We believe that a cross-language and cross-sectional analysis of Buddhist studies
literature is worthwhile for two reasons. First, various methods, perspectives and subject
matters have been studied within the international communities of Buddhist studies, and the
heterogeneity ofits scholarships can be partly explained by their geographic roots (Cabezón,
1995). It is, therefore, interesting to study empirically whether and how the intellectual
structures reflected in the published literatures in different language communities differ.
Mapping their intellectual structures can provide additional details on interests, shared and
distinct, in these three language communities. The second aspect of this study is tracing the
evolution of Buddhist studies across language communities. Although Buddhist scholarship
has a long history, the first graduate program in Buddhist studies was not offered in North
America until 1961. The formation of the International Association of Buddhist Studies in
1976 signified a further institutionalization of Buddhist studies (Swearer and Promta, 2000;
Reynolds, 1999). In the East, Buddhism has long been an established scholarship and set of
practices for thousands of years. As the broader cultural and institutional contexts of
Buddhist studiescontinue to evolve, one wonderswhether the knowledge interestsand topics
treated have also gone through substantial changes over time.
Co-word based domain analysis
Among the most crucial and arguably most challenging tasks of bibliometric-based domain
analysis is mapping the specialties or major research themes within a domain (Chen et al.,
2010). Based on co-occurrence statistics of pairs of keywords or phrases of documents in the
pertinent literature has been used to map the intellectual structure of a knowledge domain
(Callon et al., 1983, 1991).
Using co-word or other bibliographic elements to generate network to make a domain
often involves two interrelated procedures, first, a cooccurrence-based similarity measure
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Critical
thresholds
for co-word
network
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