Identifying the knowledge structure of electromagnetic fields and health research: Text network analysis and topic modeling

Abstract

Background With technological and scientific advancement, people are being increasingly exposed to electromagnetic fields, particularly from portable devices such as mobile phones. However, there is currently no consensus regarding the health effects of electromagnetic field exposure, despite the large amount of research conducted on this topic. This study aimed to understand the knowledge structure and trend of electromagnetic field and health research through text network analysis and topic modeling. Methods PubMed, Embase, and Cochrane were searched, and 3,880 articles published before June 2021 were identified. We explored the main keywords and research topics regarding electromagnetic fields and human health by constructing a network of keywords. A social network analysis program was used to analyze the data, visualize the network, and perform topic modeling. Results Four keywords, “exposure,” “effect,” “cell,” and “cancer,” were highly correlated to other keywords and formed each colony in the knowledge structure of research on electromagnetic fields and health. Five topics were derived from topic modeling: cell research, research on the adaption of MRI, health effects of mobile phones, pain therapy, and exposure measurement. Cell research has been continuously performed, and many studies have been conducted on the health effects of mobile phones since 2000. Conclusions These findings will assist in gaining insights into and understanding changes in research on the health effects of electromagnetic fields, and suggest important areas and directions for future research.