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2017 ; 12
(3
): e0172778
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Novel keyword co-occurrence network-based methods to foster systematic reviews of
scientific literature
#MMPMID28328983
Radhakrishnan S
; Erbis S
; Isaacs JA
; Kamarthi S
PLoS One
2017[]; 12
(3
): e0172778
PMID28328983
show ga
Systematic reviews of scientific literature are important for mapping the
existing state of research and highlighting further growth channels in a field of
study, but systematic reviews are inherently tedious, time consuming, and manual
in nature. In recent years, keyword co-occurrence networks (KCNs) are exploited
for knowledge mapping. In a KCN, each keyword is represented as a node and each
co-occurrence of a pair of words is represented as a link. The number of times
that a pair of words co-occurs in multiple articles constitutes the weight of the
link connecting the pair. The network constructed in this manner represents
cumulative knowledge of a domain and helps to uncover meaningful knowledge
components and insights based on the patterns and strength of links between
keywords that appear in the literature. In this work, we propose a KCN-based
approach that can be implemented prior to undertaking a systematic review to
guide and accelerate the review process. The novelty of this method lies in the
new metrics used for statistical analysis of a KCN that differ from those
typically used for KCN analysis. The approach is demonstrated through its
application to nano-related Environmental, Health, and Safety (EHS) risk
literature. The KCN approach identified the knowledge components, knowledge
structure, and research trends that match with those discovered through a
traditional systematic review of the nanoEHS field. Because KCN-based analyses
can be conducted more quickly to explore a vast amount of literature, this method
can provide a knowledge map and insights prior to undertaking a rigorous
traditional systematic review. This two-step approach can significantly reduce
the effort and time required for a traditional systematic literature review. The
proposed KCN-based pre-systematic review method is universal. It can be applied
to any scientific field of study to prepare a knowledge map.
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