Top 100 Publications as Measured by Altmetrics in the Field of Central Nervous System Inflammatory Demyelinating Disease

Biomed Res Int. 2019 Dec 2:2019:3748091. doi: 10.1155/2019/3748091. eCollection 2019.

Abstract

Background: Altmetrics analyze the visibility of articles in social media and estimate their impact on the general population. We performed an altmetric analysis of articles on central nervous system inflammatory demyelinating disease (CIDD) and investigated its correlation with citation analysis.

Methods: Articles in the 91 journals comprising the "clinical neurology," "neuroscience," and "medicine, general, and internal" Web of Science categories were searched for their relevance to the CIDD topic. The Altmetric Explorer database was used to determine the Altmetric.com Attention Score (AAS) values of the selected articles. The papers with the top 100 AAS values were characterized.

Results: Articles most frequently mentioned online were primarily published after 2014 and were published in journals with high impact factors. All articles except one were dealt with the issue of multiple sclerosis. Most were original articles, but editorials were also common. Novel treatments and risk factors are the most frequent topics. The AAS was weakly correlated with journal impact factors; however, no link was found between the AAS and the number of citations.

Conclusions: We present the top 100 most frequently mentioned CIDD articles in online media using an altmetric approach. Altmetrics can rapidly offer alternative information on the impact of research based on a broader audience and can complement traditional metrics.

MeSH terms

  • Bibliometrics*
  • Central Nervous System
  • Central Nervous System Diseases*
  • Databases, Factual / statistics & numerical data
  • Databases, Factual / trends
  • Demyelinating Diseases*
  • Humans
  • Journal Impact Factor
  • Multiple Sclerosis
  • Periodicals as Topic* / statistics & numerical data
  • Periodicals as Topic* / trends
  • Publications* / statistics & numerical data
  • Publications* / trends
  • Risk Factors
  • Social Media