Applying Social Network Analysis to Understand the Percentages of Keywords within Abstracts of Journals: A System Review of Three Journals

Abstract

Background: 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. Objective: 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. Methods: 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. Results: 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. Conclusion: 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. the accompanying abstract requires analysis. The Percentage of Keywords (PKW) within an abstract for a paper can be used to compare journals.