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Influenza Altmetric Attention Score and its association with the influenza season in the USA.

Saif Aldeen S AlRyalatKhaled Al OweidatMohammad Al-EssaKhaled AshouriOsama El KhatibAthar Al-RawashdehAbeer YaseenAhmad ToumarAnas Alrwashdeh
Published in: F1000Research (2020)
Background:  Altmetrics measure the impact of journal articles by tracking social media, Wikipedia, public policy documents, blogs, and mainstream news activity, after which an overall Altmetric attention score (AAS) is calculated for every journal article. In this study, we aim to assess the AAS for influenza related articles and its relation to the influenza season in the USA. Methods:  This study used the openly available Altmetric data from Altmetric.com. First, we retrieved all influenza-related articles using an advanced PubMed search query, then we inputted the resulted query into Altmetric explorer. We then calculated the average AAS for each month during the years 2012-2018. Results : A total of 24,964 PubMed documents were extracted, among them, 12,395 documents had at least one attention. We found a significant difference in mean AAS between February and each of January and March (p< 0.001, mean difference of 117.4 and 460.7, respectively). We found a significant difference between June and each of May and July (p< 0.001, mean difference of 1221.4 and 162.7, respectively). We also found a significant difference between October and each of September and November (p< 0.001, mean difference of 88.8 and 154.8, respectively). Conclusion:  We observed a seasonal trend in the attention toward influenza-related research, with three annual peaks that correlated with the beginning, peak, and end of influenza seasons in the USA, according to Centers for Disease Control and Prevention (CDC) data.
Keyphrases
  • social media
  • working memory
  • healthcare
  • public health
  • mental health
  • electronic health record
  • machine learning
  • emergency department
  • big data
  • health information
  • adverse drug
  • artificial intelligence
  • data analysis