Coronavirus, Ageism, and Twitter: An Evaluation of Tweets about Older Adults and COVID-19

J Am Geriatr Soc. 2020 Aug;68(8):1661-1665. doi: 10.1111/jgs.16508. Epub 2020 May 9.


Objectives: In March 2020, the World Health Organization declared coronavirus disease 2019 (COVID-19) a pandemic. High morbidity and mortality rates of COVID-19 have been observed among older adults and widely reported in both mainstream and social media. The objective of this study was to analyze tweets related to COVID-19 and older adults, and to identify ageist content.

Design: We obtained a representative sample of original tweets containing the keywords "elderly," "older," and/or "boomer" plus the hashtags "#COVID19" and/or "#coronavirus."

Setting: Tweets posted between March 12 and March 21, 2020.

Measurements: We identified the type of user and number of followers for each account. Tweets were classified by three raters as (1) informative, (2) personal accounts, (3) personal opinions, (4) advice seeking, (5) jokes, and (6) miscellaneous. Potentially offensive content, as well as that downplaying the severity of COVID-19 because it mostly affects older adults, was identified.

Results: A total of 18,128 tweets were obtained, of which a random sample of 351 was analyzed. Most accounts (91.7%) belonged to individuals. The most common types of tweets were personal opinions (31.9%), followed by informative tweets (29.6%), jokes/ridicule (14.3%), and personal accounts (13.4%). Overall, 72 tweets (21.9%) likely intended to ridicule or offend someone and 21.1% had content implying that the life of older adults was less valuable or downplayed the relevance of COVID-19.

Conclusion: Most tweets related to COVID-19 and older adults contained personal opinions, personal accounts, and jokes. Almost one-quarter of analyzed tweets had ageist or potentially offensive content toward older adults. J Am Geriatr Soc 68:1661-1665, 2020.

Keywords: COVID-19; Twitter messaging; ageism; geriatrics; social media.

Publication types

  • Evaluation Study

MeSH terms

  • Aged
  • Aged, 80 and over
  • Ageism / trends*
  • Betacoronavirus*
  • COVID-19
  • Coronavirus Infections / psychology*
  • Female
  • Humans
  • Male
  • Pandemics
  • Pneumonia, Viral / psychology*
  • SARS-CoV-2
  • Social Media / trends*