JUNIPER PUBLISHERS-Current Trends in Biomedical Engineering & Biosciences
Applying Social Network Analysis to Understand the Percentages of Keywords within Abstracts of Journals: A System Review of Three Journals
Authored by Willy Chou*
Academic literature suggests keywords
that are retrieved from a paper’s title and abstract represent important
concepts in that study. The percentage of keywords within an abstract (PKWA) is
required to investigate. To compare the PKWA in journals of medical informatics
and the keyword network relationship in order to develop a self-examining
policy for the journal. Selecting 5,985 abstracts and their corresponding
keywords in three journals (JMIR, JAMIA, and BMC Med Inform Decis Mak.)
published between 1995 to 2017(April) on the US National Library of Medicine
National Institutes of Health (Pubmed.org), we computed the PKWA for each
journal by using MS Excel modules and compared the percentage differences
across journals and years via a two-way ANOVA. Social Network Analysis (SNA)
was performed to explore the relations of keywords in journals. The PKWA are
48.81, 41.59, and 56.84 for the three journals, respectively. A statistically
significant difference (p<0.05) is found in the percentages among journals
selected. In contrast, no differences (p>0.05) are found (1) between years
(2016 and 2017) and (2) in interaction effects between journals and years.
Three journals display significantly different patterns in network keywords and
major cohesion measures. It is required to apply the computer module when
inspecting whether keywords are within abstracts. The cohesion measure provides
journal editors with a method of examining keywords within an abstract for a
paper under review.
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