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Social media discourse on ageism, sexism, and racism: Analysis of 150 million tweets over 15 years.
Ng, Reuben; Indran, Nicole; Liu, Luyao.
Affiliation
  • Ng R; Lee Kuan Yew School of Public Policy, National University of Singapore, Singapore, Singapore.
  • Indran N; Lloyd's Register Foundation Institute for the Public Understanding of Risk, National University of Singapore, Singapore, Singapore.
  • Liu L; Lee Kuan Yew School of Public Policy, National University of Singapore, Singapore, Singapore.
J Am Geriatr Soc ; 2024 Jul 03.
Article in En | MEDLINE | ID: mdl-38958541
ABSTRACT

BACKGROUND:

Ageism is a major but oft-overlooked social determinant of health. In fact, it is widely accepted among scholars that ageism is one of the least acknowledged forms of inequality, although few empirical attempts have been made to substantiate this claim. This is the first study that quantifies the amount of discourse dedicated to ageism, sexism, and racism on Twitter. Specifically, we rely on the usage of hashtags as a proxy for the frequency of discussions surrounding each form of inequality over a 15-year period from 2007 to 2022. We also identify key events that triggered spikes in Twitter activity for each form of inequality.

METHODS:

Hashtags related to racism and sexism were extracted from past scholarship. We also employed a snowball sampling method whereby we queried the hashtags using Twitter's search function to identify other hashtags. As limited research has been conducted on ageism-related hashtags, we queried hashtags utilized by advocacy groups and adopted a snowball sampling method to compile other relevant hashtags. Tweets collected (N = 154,353,047) spanned 15 years, from August 23, 2007 to December 31, 2022.

RESULTS:

From 2007 to 2022, racism-related hashtags were used the most, followed by sexism-related hashtags and ageism-related hashtags. Racism-related hashtags (N = 99,250,348) were mentioned about 60 times more than ageism-related hashtags (N = 1,648,926). Sexism-related hashtags (N = 38,933,113) were mentioned 24 times more than ageism-related hashtags. The increasing linear trend of tweets associated with ageism (p < 0.001), sexism (p < 0.05), and racism (p < 0.05) reached significance. Incidents of racism and sexism often generated widespread public outrage. Conversely, instances of ageism rarely caused spikes in social media activity. Rather, these spikes were mainly observed during events such as the release of a report on ageism, a conference related to aging, or observances such as International Day of Older Persons.

CONCLUSION:

There is a need to hasten moves to raise awareness of ageism. To ensure that discussions on ageism are not confined to academic and policy circles, advocacy campaigns could be held to educate the public on the issue and its negative concomitants.
Key words

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: J Am Geriatr Soc Year: 2024 Document type: Article Affiliation country: Singapur

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: J Am Geriatr Soc Year: 2024 Document type: Article Affiliation country: Singapur