Wednesday, 5 October 2016

Impact of Social Sciences – The number behind the number: suggesting a truer measure of academic impact


The number behind the number: suggesting a truer measure of academic impact

ccarrollphotoThe limitations of simple ‘citation count’ figures are well-known. Chris Carroll
argues that the impact of an academic research paper might be better
measured by counting the number of times it is cited within citing
publications rather than by simply measuring if it has been cited or
Three or more citations of the key paper arguably represent a rather different level of impact than a single citation. By
looking for this easily generated number, every researcher can quickly
gain a greater insight into the impact (or not) of their published work.
The academic research and policy agenda
increasingly seeks to measure and use ‘impact’ as a means of determining
the value of different items of published research. However, there is much debate about how best to define and quantify impact,
and any assessment must take into account influence beyond the limited
bounds of academia, in areas such as public policy. However, within
academia, it is generally accepted that the number of times a paper is
cited, the so-called ‘citation count’ or ‘citation score’, offers the
most easily measured guide to its impact. The underlying assumption is
that the cited work has influenced the citing work in some way, but this
metric is also viewed as practically and conceptually limited. The
criticism is loud and frequent: such citation scores do not tell us how a
piece of research has actually been used in practice, only that it is
known and cited.
beyond-measureImage credit: beyond measure by frankieleon. This work is licensed under a CC BY 2.0 license.
Is there a better solution?
So, the obvious answer is to see if there
is an easy way to measure how a paper has been used by its citing
publications, rather than simply recording whether it is cited (the
standard ‘citation score’). I did this by using one of my own frequently-cited papers as a case study
and applying a basic metric: impact of the case study paper was
considered to be ‘high’ if it was cited three or more times within the
citing publication; ‘moderate’ if cited twice; and ‘low’ if cited only
The case study paper had 393 unique
citations by November 2015: 59% (230/393) of publications cited the
paper only once, suggesting its impact on these publications was low;
17% (65/393) cited it twice, suggesting moderate impact; but 25%
(98/393) cited it three or more times, suggesting that this paper was
having a genuine influence on those studies. The citation frequency
within this ‘high impact’ group of publications ranged from three to as
many as 14 in peer-reviewed studies and 17 in academic dissertations
(with their longer word count). Primary research studies published in
peer-reviewed journals were the principal publication type across all
levels of impact.
I also noted where these single or
multiple citations appeared within these publications. Single citations
tended to appear only in the introduction or background sections of
papers. These instances appeared to be simple citations ‘in passing’,
the necessary ‘nod’ to existing literature at the start of a
publication. However, when there were three or more citations, they
tended to appear across two or more sections of a paper, especially in
the methods and discussions, which suggests some real influence on the
justification or design of a study, or the interpretation of its
results. These findings on the location of the citations confirmed that
the number of times a paper was cited within a publication really was a
good indicator of that paper’s impact.
Pros and cons
A metric based on within-publication
citation frequency is unambiguous and thus capable of accuracy. The
assessment of where the citations appear in the citing publications also
provided contextual information
on the nature of the citation. In this case, it confirmed the viability
of within-publication citation frequency as an impact metric. The
approach is transparent and data can be verified and updated. The
proposed metric, the ‘citation profile’, is not a measure of research
quality, nor does it seek to measure other forms of impact or to address
issues such as negative findings producing relatively lower citation
scores. It merely seeks to contribute to the debate about how citation
metrics might be used to give a more contextually robust picture of a
paper’s academic impact.
Of course, even this ‘citation profile’ is not without its problems, but it is arguably less of a “damned lie” or “statistic”
than some other metrics: only a more in-depth analysis of each citing
publication can more accurately gauge a paper’s influence on another
piece of research or a policy document. Yes, there are also questions
concerning this metric’s generalisability: as with other bibliometrics,
publications in different disciplines are also likely to have different
citation profiles. However, these issues can be easily addressed by
future research, given the simplicity of the metric.
If academics or funders want to improve
their understanding of how research is used, then this easy-to-generate
metric can add depth and value to the basic, much-maligned, and ‘damned’
‘citation score’.
This blog post is based on the author’s article, ‘Measuring
academic research impact: creating a citation profile using the
conceptual framework for implementation fidelity as a case study’
, published in Scientometrics (DOI: 10.1007/s11192-016-2085-0).
Note: This article gives the views of
the author(s), and not the position of the LSE Impact Blog, nor of the
London School of Economics. Please review our 
comments policy if you have any concerns on posting a comment below.
About the author
Chris Carroll is a Reader
in Systematic Review and Evidence Synthesis at the University of
Sheffield. His role principally involves synthesising published data to
help inform policymaking, particularly in the fields of medicine and
health, as well as the development of methods to conduct such work.

Impact of Social Sciences – The number behind the number: suggesting a truer measure of academic impact

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