Study on the research evolution of Nobel laureates 2018 based on self-citation network

DOIhttps://doi.org/10.1108/JD-02-2019-0027
Date26 September 2019
Pages1416-1431
Publication Date26 September 2019
AuthorFangfang Wen
SubjectLibrary & 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
Study on the research evolution of
Nobel laureates 2018 based on
self-citation network
Fangfang Wen
School of Management,
Henan University of Science and Technology, Luoyang, China
Abstract
Purpose Science is a continuum of experiences consisting of authors and their publications, and the
authorsexperience is an integral part of their work that gets reflected through self-citations. Thus, self-
citations can be employed in measuring the relevance between publications and tracking the evolution of
research. The paper aims to discuss this issue.
Design/methodology/approach Based on the bibliographic data obtained from Scopus, this study
constructs and visualizes the self-citation networks of ten Nobel laureates 2018, in the fields of Physiology or
Medicine, Physics, Chemistry and Economic Science, to demonstrate the evolving process of each laureates
research across his or her scholarly career.
Findings Statistics indicate that prominent scientists, such as Nobel laureates, have also frequently cited
their own publications. However, their self-cited rates are quite low. Self-citations constitute an indispensable
part of the citation system but contribute little to authorsscientific impact, regardless of artificial
self-citations. Self-citation networks present a trajectory that shows the evolving process of research across a
scientists long-term scholarly career. There are obvious differences in self-citation patterns and network
structures of different laureates without a disciplinary difference observed. The structures of self-citation
networks are significantly influenced by laureatesproductivity. In addition, it is laureatesown research
patterns and citation habits that lead to the diversified patterns and structures of self-citation networks.
Research limitations/implications Only scientific achievements presented in the form of publications
are investigated and other kinds of scientific output, such as patents, are not included. Moreover, this
approach is fit for scientists who have had a longer career and higher productivity.
Originality/value This study proves the feasibility and effectiveness of self-citation analysis as a new way
to examine research evolution.
Keywords Citation analysis, Bibliometrics, Information management, Self-citation, Scientometrics,
Research evolution
Paper type Research paper
Introduction
Science is a continuum of experiences consisting of authors and their publications, and the
authorsexperience is an integral part of theirwork that gets reflected through self-citations.
There is hardly an authorwho does not make use of his or her own work. So, self-citation is a
prevalent phenomenon in the scientific community. Though varying by discipline and by
origin of publication, average self-citation rates between10 and 40 percent are common (Thijs
and Glänzel, 2006). It is reasonable and necessary that self-citation should occur when an
author refers to relevant previous work or avoidsrepetition of previous experimentalset-ups
(Brown, 2009). As a natural result of the way in which scientific work builds upon previous
scientific work, self-citation is deemed a regular and indispensable part of scientific
communication, since it reflects the continuous and cumulative nature of research process
(Pichappan and Sarasvady, 2002). However, from the viewpoint of scientific evaluation,
self-citations may be considered as a source of noise or distortion that affects the validity of
using citations as a measure of scientific impact (Schubert et al., 2006), on the grounds that
Journal of Documentation
Vol. 75 No. 6, 2019
pp. 1416-1431
© Emerald PublishingLimited
0022-0418
DOI 10.1108/JD-02-2019-0027
Received 12 February 2019
Revised 11 May 2019
Accepted 15 May 2019
The current issue and full text archive of this journal is available on Emerald Insight at:
www.emeraldinsight.com/0022-0418.htm
This paper is funded by the Planning Project for Philosophy and Social Science of Henan Province
(No. 2018CZH012).
1416
JD
75,6
self-citation does not reveal anything about the impact of a work beyond its own producers
and it also hasthe risk of being manipulatedby editors and authors withutilitarian intentions.
Self-citation is a non-negligible phenomenon usually surrounded by dispute. Supporters
believe that self-citations reflect the inheritance and coherence of scientific research.
Opponents argue that self-citations have a negative effect on the evaluation of scientific
impact by artificially amplifying some citation-based indicators. The reason for the dispute
is that people examine self-citation from different perspectives. As Garfield (1979)
suggested, self-citation has nothing to do with good or bad; what matters is how we view it
and how we use it. However, previous studies on self-citation have been viewed mostly from
the scientific evaluation aspects. Most studies focus on how prevalent self-citation is and
how it influences citation-based indicators, often ignoring its function as a mechanism of
relevant knowledge diffusion and its usefulness at guiding readers in finding new relevant
scientific knowledge (Gálvez, 2017). Given the cumulative nature of new knowledge
production, self-citations constitute a natural part of communication. Scientists build upon
their own results with self-citations representing the use of prior results in present research
(Costas et al., 2010). Self-citation can also serve necessary functions, such as allowing
authors to refer to previously established methodologies and to provide justification or
support for future studies based on their previous publications (Larcombe and Voss, 2011).
As stated by Wojick et al. (2006), scientific publication is a huge system of deliberate
knowledge diffusion. In consequence, citations have played a key role in recording how
researchers utilize existing knowledge and have beenconsidered to be one of themain drivers
of scientific knowledge diffusion (Yu et al., 2010). Among which, s elf-citations also facilitate
knowledge ow and diffusion (Yu et al., 2014). A closed network of self-citing and self-cited
paperscan reveal importantaspects of the developmentof scientific work(Hellsten et al., 2007).
Therefore, successive papers linked by self-citation relationships constitute a chain which can
show the evolution of science. This means that self-citation can be applied to display the
research trajectory of scientists, as well as to track the mobility of their research. One scientist,
especiallya prominent scholarwith a relativelylong publicationhistory, has a set of successive
papersrecording and reflecting his or herresearch in differentphases of scholarlycareer; some
of them are connected by self-citations. Self-citation is an org anic part of the citation process,
obeying rules that can be measured and described with the help of mathematical models
(Glänzel et al., 2004). Thus, this study proposes an approach to investigate and visualize
research trajectory by self-citation network. Taking 10 Nobel laureates 2018 in the fields of
Physiology or Medicine, Physics, Chemistry and Economic Science as examples, this study
exploits the self-citation patterns of these prominent scientists and detects the research
evolvingtrajectories of theirscholarly career by constructing andvisualizing theirself-citation
networks, based on the bibliographic data extracted from Scopus.
Literature review
Definitions and indicators of self-citation
Self-citation is usually defined as a citation in which the citing and the cited paper have at least
one author in common (Aksnes, 2003). Self-citation can take place at many different levels and
result in different kinds of self-citations, including author self-citation, institution self-citation,
region (country) self-citation, journal self-citation, discipline (research field) self-citation and
languageself-citation(Egghe et al., 1999; Thijs and Glanzel, 2006; Hendrix, 2009; Gul et al., 2017;
Bakare and Lewison, 2017). Among them, author self-citation and journal self-citation are the
focus of bibliometric analysis. Authorself-citation is a situation in whichany of the authors of
an original article shares a name with an author of any article that cites the original article or is
cited by it (Snyder and Bonzi, 1998). ISI denes self-citing rate as the ratiobetween the number
of times a journal citesitself and the number oftotal references it makes; and the self-cited rate
is defined as thenumber of times it is cited by itself overall citations by all journals including
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Research
evolution of
Nobel
laureates 2018

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