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Self-citation by researchers: narcissism or an inevitable outcome of a cohesive and sustained research program?

iee 7 (2014) 1
Ideas in Ecology and Evolution 7: 1±2, 2014
2014 The Author.
Ideas in Ecology and Evolution 2014
Received 12 January 2014; Accepted 16 January 2014
Self-citation by resear chers: narciss ism or an inevitable outcome of a cohesive
and sustained resea rch progr am?
Steven J. Cook e and M ichael R . Donaldson
teven J. Cooke (steven_cooke @ca, F ish E cology and Conservation Physiology Laboratory, Depart
of Biology and Institute of E nvi ron
cience, C arleton University, Ottawa, Ontario, Canada
Michael R. D onaldson (
), Depart
ent of Natural Resourc es and Environ
ciences, University of Il linois, Urbana, Illinois, U
The research community remains focused with
enumerating, evaluating, and ranking the research
productivity of individual authors despite the apparent
shortcomings of doing so. Basic yet widely used citation
metrics such as ³WRWDO FLWHV´ (Adam 2002) or ³+LUsch (h)
LQGH[´ (Hirsch 2005) require a count of the number of
times that a given DXWKRU¶V works are cited. Fortunately
there are a variety of electronic bibliometric tools (e.g.,
Web of Science, Google Scholar, Scopus) that do that
work for us. Interestingly, those tools tend to generate
default counts that can include self-citations. Self-
citations can be defined as occurrences in which the
citing and cited papers share at least one author in
common (Asknes 2003), although various definitions
have been proposed (Fowler and Aksnes 2007, Costas et
al. 2010). Self-citations can be easily filtered out with a
few clicks to generate ³FRUUHFWHG´ indices (e.g.,
Schreiber 2007, Brown 2009) or those that discount
self-cites (e.g., Ferrara and Romero 2013), but is it
necessary to do so? Here, we argue that self-citations
need not necessarily be considered a form of narcissistic
behavior, and instead could be indicative of a cohesive
research program, in which authors refer to their prev-
ious relevant works in order to enhance their subsequent
contributions to knowledge.
When applying for scientific positions, promotions,
tenure, or awards, one must decide whether they will
report their ³SURGXFWLYLW\´ with or without self-citations,
or include both. And, those assessing such researchers
must decide which they wish to consider and whether
they will ³SHQDOL]H´ someone that fails to exclude self-
citations. Some individuals may feel that it is abhorrent
to include self-citations while others may be indifferent.
On the surface, ³VHOI-FLWDWLRQ´ may appear to border on
narcissism. However, the argument could also be made
that self-citation is in fact an indicator of RQH¶V promin-
ence and productivity in their field. Consider a research-
er with a focused research program publishing year after
year on related topics, with papers building upon ideas
and discoveries codified in previous work. One would
expect significant reliance on research papers from the
same research lab. Indeed, is that not what an ³LGHDO´
research program should look like? Similarly, if one is
working in a highly specialized field where there is
simply little other research effort, self-citation would be
essential. The more productive one is in terms of output
in quantity of papers would also inherently lead to
greater potential for self-citations. In this sense, it is
reasonable to think that self-citation itself could be used
as an indicator of the extent to which one has a cohesive
and coordinated research program, with the extent of
self-citation scaling with extent of output (in number of
papers) from a research program.
When building a research program, self-citations can
be an important aspect of developing a cohesive
knowledge base and moving science forward. For
example, if a research program has already been estab-
lished, either by the author themselves or their col-
laborators and co-authors, it follows that self-citations
would be necessary to develop the rationale that the
current work is building on previously accumulated
knowledge. Likewise, when interpreting findings by
drawing on existing literature, self-citations are often
necessary. For example, depending on the field of study
and research questions being asked, the existing
literature may be predominated by the DXWKRU¶V own
This work is licensed under a Creative Commons Attribution 3.0 License.
iee 7 (2014) 2
research team, requiring self-citations (e.g., emerging
fields of study like molecular ecology). Thus, self-
citations can serve the dual purpose of providing
rationale for the present work and also incrementing the
knowledge provided by existing work. In this sense,
self-citation could indicate a cohesive research program.
A unified body of knowledge could in turn influence
others (Donaldson and Cooke 2014). Indeed, Fowler
and Aksnes (2007) show that the more one cites oneself,
the more one is cited by others.
There are certainly instances where self-citation
would be considered problematic. The potential for
egregious self-citations exists (i.e., authors that go out of
their way to cite their own work, even if only tangent-
ially related), the onus for avoiding the manipulation of
self-citations falls on the authors, or at the very least is
something that should be corrected at the peer-review
stage, prior to publication. There are also a number of
strategies for identifying egregious attempts to manip-
ulate bibliometrics through self-citation analysis
(Bartneck and Kokkelmans 2011). Likewise, a research-
er could intentionally cite their own work while failing
to consider the broader literature. Such behaviour would
be especially egregious if the research area is well
developed. In the most insidious cases this could be
done by researchers to directly manipulate their citation
metrics (Testa 2008). However, it could also be done by
a naïve researcher and simply reflect a lack of
familiarity with relevant literature. Yet, conversely,
failing to cite RQH¶V own work if and when it is the most
relevant reference is no different than not citing some-
one HOVH¶V key paper. That is, intentionally avoiding
self-citation should not be the norm.
Trying to discern whether individual self-citation pat-
terns are legitimate is probably best achieved at the level
of an individual paper as judged by knowledgeable
referees and astute, experienced editors (Cooke and
Lapointe 2012). Has the author used a diversity of ref-
erences, paying homage to the classic foundational work
while simultaneously including contemporary refer-
ences? Extensive self-citation may not be inherently
wrong if the referees and editor judge that the references
used (both self-citations and others) are indeed the most
relevant references. If the scientific community serves
as a filter to unwarranted self-citations during the peer
review process, then we argue that self-citations²no
matter the extent²are relevant and should be included
as overall measures of a UHVHDUFKHU¶V productivity and
influence in that it is an inevitable outcome of a
coordinated, sustained and productive research program.
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pay? Scientometrics. 72: 427±437. CrossRef
scientific research output. Proceedings of the
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America 102: 16569±16572. CrossRef
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... For this exercise, we considered all citations (including self-citations). We did so not only because it is the most common procedure in evaluations (particularly when the number of people being evaluated is large), but also and mainly because self-citations are expected to result from of a cohesive research program, in which authors must refer to their previous papers to justify subsequent contributions to knowledge (Cooke & Donaldson, 2014), and can be considered equally important as cites from others (Kacem et al., 2020). In high-standard journals it is expected that reviewers and editors judge, among many other things, that the authors used the most relevant references and, in that context, it should be assumed in principle that self-citation may not be simply a misconduct (that naturally may also be the case; Bartneck & Kokkelmans, 2011;Ioannidis, 2015). ...
Aim of study: A common procedure when evaluating scientists is considering the journal’s quartile of impact factors (within a category), many times considering the quartile in the year of publication instead of the last available ranking. We tested whether the extra work involved in considering the quartiles of each particular year is justified Area of study: Europe Material and methods: we retrieved information from all papers published in 2008-2012 by researchers of AGROTECNIO, a centre focused in a range of agri-food subjects. Then, we validated the results observed for AGROTECNIO against five other European independent research centres: Technical University of Madrid (UPM) and the Universities of Nottingham (UK), Copenhagen (Denmark), Helsinki (Finland), and Bologna (Italy). Main results: The relationship between the actual impact of the papers and the impact factor quartile of a journal within its category was not clear, although for evaluations based on recently published papers there might not be much better indicators. We found unnecessary to determine the rank of the journal for the year of publication as the outcome of the evaluation using the last available rank was virtually the same. Research highlights: We confirmed that the journal quality reflects only vaguely the quality of the papers, and reported for the first time evidences that using the journal rank from the particular year that papers were published represents an unnecessary effort and therefore evaluation should be done simply considering the last available rank.
... A more aggressive strategy involves penalizing, which some favor, but in practice, this would likely trigger scientifically unjustifiable levels of self-censorship. Furthermore, policing would provoke endless debates over what qualifies as bad behavior and may criminalize warranted self-citations that are a result of coordinated, sustained, and productive research efforts [16]. Penalizing is either technically insufficient or excessively stigmatizing and does not take into account that each disciplinary community will have its own standards of appropriateness with respect to the use of self-citations. ...
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Who among the many researchers is most likely to usher in a new era of scientific breakthroughs? This question is of critical importance to universities, funding agencies, as well as scientists who must compete under great pressure for limited amounts of research money. Citations are the current primary means of evaluating one's scientific productivity and impact, and while often helpful, there is growing concern over the use of excessive self-citations to help build sustainable careers in science. Incorporating superfluous self-citations in one's writings requires little effort, receives virtually no penalty, and can boost, albeit artificially, scholarly impact and visibility, which are both necessary for moving up the academic ladder. Such behavior is likely to increase, given the recent explosive rise in popularity of web-based citation analysis tools (Web of Science, Google Scholar, Scopus, and Altmetric) that rank research performance. Here, we argue for new metrics centered on transparency to help curb this form of self-promotion that, if left unchecked, can have a negative impact on the scientific workforce, the way that we publish new knowledge, and ultimately the course of scientific advance.
... The h-index can also be increased artificially by self-citations (Bartneck & Kokkelmans, 2011;Ferrara & Romero, 2013). Caution and careful discernment is necessary when analyzing for selfcitations; large self-citations can be the outcome of a cohesive and sustained research program (Cooke & Donaldson, 2014), the exact kind of research program one would hope to see from VPRs. This risk, however, is magnified if Google Scholar is used as the automated values can be easily manipulated with paper generators like SCIgen, which produce nonsense written output (Labbe, 2010). ...
University tuition fees and student debt have risen in part due to rapid expansion of university administration compensation. This study provides a novel methodology for detecting inappropriate executive compensation within universities. The usefulness of academic ideas is openly ranked using the h-index. By comparing the ratio of academic executive pay to their h-index a dollar per value of academic impact can be found. If the university compensation system is appropriately calibrated, the impact/$ increases with faculty rank and continues to improve into the executive team. Analysis is provided for vice presidents of research of the ten largest state universities in America. The results suggest that 50% of these public universities are overcompensating their executives. A case study is presented of the most egregious discrepancy around compensation of >$3.1 million/year. The methodology was shown to be a quick and inexpensive way to ascertain if further investigation is necessary at an individual university.
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Citation metrics have value because they aim to make scientific assessment a level playing field, but urgent transparency-based adjustments are necessary to ensure that measurements yield the most accurate picture of impact and excellence. One problematic area is the handling of self-citations, which are either excluded or inappropriately accounted for when using bibliometric indicators for research evaluation. Here, in favor of openly tracking self-citations we report on self-referencing behavior among various academic disciplines as captured by the curated Clarivate Analytics Web of Science database. Specifically, we examined the behavior of 385,616 authors grouped into 15 subject areas like Biology, Chemistry, Science & Technology, Engineering, and Physics. These authors have published 3,240,973 papers that have accumulated 90,806,462 citations, roughly five percent of which are self-citations. Up until now, very little is known about the buildup of self-citations at the author-level and in field-specific contexts. Our view is that hiding self-citation data is indefensible and needlessly confuses any attempts to understand the bibliometric impact of one's work. Instead we urge academics to embrace visibility of citation data in a community of peers, which relies on nuance and openness rather than curated scorekeeping.
Researchers have investigated factors thought to affect the total number of citations in various academic disciplines, and some general trends have emerged. However, there are still limited data for many fields, including aquatic sciences. Using papers published in 2003–2005 (n = 785), we investigated marine and freshwater biology articles to identify factors that may contribute to the probability of citation and for cumulative citation counts over 10 years. We found no relationships with probability of citation; however, we found evidence that for those that were cited at least once, cumulative citations were related to several factors. Articles cited by books received more citations than those never cited by books, which we hypothesized to be indicative of the impact an article may have in the field. We also found that articles first cited within 2 years of publication received more cumulative citations than those first cited after 2 years. We found no evidence that self-citation (as the first citation) had a significant effect on total citations. Our findings were compared with previous studies in other disciplines, and it was found that aquatic science citation patterns are comparable to fields in science and technology but less so to humanities and social sciences.
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In this paper, we propose a measure to assess scientific impact that discounts self-citations and does not require any prior knowledge on the their distribution among publications. This index can be applied to both researchers and journals. In particular, we show that it fills the gap of h-index and similar measures that do not take into account the effect of self-citations for authors or journals impact evaluation. The paper provides with two real-world examples: in the former, we evaluate the research impact of the most productive scholars in Computer Science (according to DBLP); in the latter, we revisit the impact of the journals ranked in the 'Computer Science Applications' section of SCImago. We observe how self-citations, in many cases, affect the rankings obtained according to different measures (including h-index and ch-index), and show how the proposed measure mitigates this effect.
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The h-index has received an enormous attention for being an indicator that measures the quality of researchers and organizations. We investigate to what degree authors can inflate their h-index through strategic self-citations with the help of a simulation. We extended Burrell's publication model with a procedure for placing self-citations, following three different strategies: random self-citation, recent self-citations and h-manipulating self-citations. The results show that authors can considerably inflate their h-index through self-citations. We propose the q-index as an indicator for how strategically an author has placed self-citations, and which serves as a tool to detect possible manipulation of the h-index. The results also show that the best strategy for an high h-index is publishing papers that are highly cited by others. The productivity has also a positive effect on the h-index.
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This paper focuses on the study of self-citations at the meso and micro (individual) levels, on the basis of an analysis of the production (1994-2004) of individual researchers working at the Spanish CSIC in the areas of Biology and Biomedicine and Material Sciences. Two different types of self-citations are described: author self-citations (citations received from the author him/herself) and co-author self-citations (citations received from the researchers' co-authors but without his/her participation). Self-citations do not play a decisive role in the high citation scores of documents either at the individual or at the meso level, which are mainly due to external citations. At micro-level, the percentage of self-citations does not change by professional rank or age, but differences in the relative weight of author and co-author self-citations have been found. The percentage of co-author self-citations tends to decrease with age and professional rank while the percentage of author self-citations shows the opposite trend. Suppressing author self-citations from citation counts to prevent overblown self-citation practices may result in a higher reduction of citation numbers of old scientists and, particularly, of those in the highest categories. Author and co-author self-citations provide valuable information on the scientific communication process, but external citations are the most relevant for evaluative purposes. As a final recommendation, studies considering self-citations at the individual level should make clear whether author or total self-citations are used as these can affect researchers differently.
Scientists' work is often evaluated using citation statistics compiled by a company called the ISI. But how useful and reliable are the data? David Adam gets the measure of citation analysis.
I propose to sharpen the index h, suggested by Hirsch as a useful index to characterize the scientific output of a researcher, by excluding the self-citations. Performing a self-experiment and also discussing in detail two anonymous data sets, it is shown that self-citations can significantly reduce the h index in contrast to Hirsch's expectations. This result is confirmed by an analysis of 13 further data sets.
CrossRef Brown, R.J.C. 2009. A simple method for excluding self-citation from the h-index: the b-index
  • D W Aksnes
  • C Bartneck
  • S Kokkelmans
Aksnes, D.W. 2003. A macro study of self-citation. Scientometrics 56: 235246. CrossRef Bartneck, C., and S. Kokkelmans. 2011. Detecting hindex manipulation through self-citation analysis. Scientometrics 87: 8598. CrossRef Brown, R.J.C. 2009. A simple method for excluding self-citation from the h-index: the b-index. Online Information Review 33: 11291136. CrossRef
Does self-citation pay? Scientometrics. 72: 427 437. CrossRef scientific research output
  • J H Fowler
  • D W Aksnes
Fowler, J.H., and D.W. Aksnes. 2007. Does self-citation pay? Scientometrics. 72: 427 437. CrossRef scientific research output. Proceedings of the National Academy of Sciences of the United States of America 102: 16569 16572. CrossRef