Four Facets to Know a Cancer Care-related Journal: An Example of Eur. J. Cancer Care (Engl.)

Abstract

Objective: This study aimed to investigate the journal features by collecting some data from Pubmed Central (PMC) and to interpret the characteristics of the journal for Eur J Cancer Care (Engl) (EJCC). Methods: Selecting 1611 abstracts and their corresponding author names and keywords on September 3, 2017, from PMC, we analyzed data mentioned above to address following features: (1) Nation distribution and author collaborations; (2) Journal features represented by article keywords; (3) The most productive authors and their authorship clusters; (4) The top 10 journals most similar to EJCC. Microsoft Excel VBA routines were programmed to extract data from PMC. Rasch model and SNA Pajek software were used to present visualized displays for EJCC features. Results: We found (1) the majority of the articles are from UK (28%) Australia (10%) and Sweden (5%); (2) The most linked Keywords are cancer and breast cancer; (3) The most productive author is R Sanson-Fisher; (4) The top one journal with the most similarity to EJCC is Support Care Cancer. Conclusion: Social network analysis that provides wide and deep insight into the relationships among nations, coauthor collaborations, abstract keywords and journals most similar to EJCC was performed in this study. The results can be provided to strategy and decision making for the target journal in the future.