BACKGROUND
Researchers often spend a great deal of time and effort retrieving related articles for their studies and submissions. Article authors often designate one article and then retrieve other articles that are related to the given one using PubMed’s service for finding similar articles. However, to date, none present the pattern seen in selecting related journals as similar to a given journal. Authors need one effective and efficient way to find similar journals to the designated journal selected for a study.
OBJECTIVE
The aim of this study is to (1) show the location of related journals for a given journal online using Google Maps; (2) to verify the change in those related journals, along with their respective impact factors; and (3) to inspect the features of network density indices among clusters separated by social network analysis (SNA).
METHODS
Using downloaded abstracts from the Medline library for the Journal of Medical Internet Research (JMIR) published in 2007 and 2017, we plotted the clusters of related journals on Google Maps by using MS Excel modules, and we compared the features of network density indices. The Kendall coefficient (W) was used to assess the concordance of clusters across indices.
RESULTS
This study found that (1) the journals related to JMIR are easily presented on Google Maps; (2) no difference was found in the medians of impact factor on related journals between the years of 2007 and 2017 (3.01(2.62–3.40) and 2.55(2.29–2.82), respectively); and (3) All but the ratio indices in 2007 have a statistically significant concordance (p < 0.05).
CONCLUSIONS
SNA provides deep insight into the relationships of related journals to a given journal. The results of this research can provide readers with a knowledge and concept diagram to use with future submissions to a given journal in the subject category of medical informatics.