Research Interest and Public Interest in Melanoma: A Bibliometric and Google Trends Analysis

Abstract

Introduction: Melanoma is a severe skin cancer that metastasizes quickly. Bibliometric analysis can quantify hotspots of research interest. Google Trends can provide information to address public concerns.

Methods: The top 15 most frequently cited articles on melanoma each year from 2015 to 2019, according to annual citations, were retrieved from the Web of Science database. Original articles, reviews, and research letters were included in this research. For the Google Trends analysis, the topic "Melanoma" was selected as the keyword. Online search data from 2004 to 2019 were collected. Four countries (New Zealand, Australia, the United States and the United Kingdom) were selected for seasonal analysis. Annual trends in relative search volume and seasonal variation were analyzed, and the top related topics and rising related topics were also selected and analyzed.

Results: The top 15 most frequently cited articles each year were all original articles that focused on immunotherapy (n=8), omics (n=5), and the microbiome (n=2). The average relative search volume remained relatively stable across the years. The seasonal variation analysis revealed that the peak appeared in summer, and the valley appeared in winter. The diseases associated with or manifestations of melanoma, treatment options, risk factors, diagnostic tools, and prognosis were the topics in which the public was most interested. Most of the topics revealed by bibliometric and Google Trends analyses were consistent, with the exception of issues related to the molecular biology of melanoma.

Conclusion: This study revealed the trends in research interest and public interest in melanoma, which may pave the way for further research.

Keywords: Google Trends; bibliometric analysis; melanoma; public interest; research interest.

Figure 1

Annual trends (A) and seasonal variation (B) of the relative search volume on melanoma. a. Annual trends from 2004 to 2019. (B) Seasonal variation in New Zealand, Australia, the United Kingdom, and the United States. (A) The lines represent the overall trend of RSV variation, and the circles represent the data points of the 12-month average RSV for each year. (B) The seasonal analysis was conducted and fit by the cosinor model with a p-value < 0.05. The arrows indicate the extreme value of the 16-year average RSV. (Box: interquartile range (IQR). The horizontal line inside each box: median. Whisker: maximum and minimum within median ± 1.5 × IQR. Circle: outlier outside 1.5 IQR.)