World Pneumonia Day 2011-2016: Twitter contents and retweets

Md Mohiuddin Adnan, Jingjing Yin, Ashley M. Jackson, Zion Tsz Ho Tse, Hai Liang, King Wa Fu, Nitin Saroha, Benjamin M. Althouse, Isaac Chun Hai Fung

Research output: Contribution to journalArticlepeer-review

7 Scopus citations

Abstract

Background: Twitter is used for World Pneumonia Day (WPD; November 12) communication. We evaluate if themes of #pneumonia tweets were associated with retweet frequency. Methods: A total of 28 181 original #pneumonia tweets were retrieved (21 November 2016), from which six subcorpora, 1 mo before and 1 mo after WPD 2011-2016, were extracted (n=6721). Underlying topics were identified via latent Dirichlet allocation and were manually coded into themes. The association of themes with retweet count was assessed via multivariable hurdle regression. Results: Compared with personal experience tweets, tweets that both raised awareness and promoted intervention were 2.62 times as likely to be retweeted (adjusted odds ratio [aOR] 2.62 [95% 1.79 to 3.85]) and if retweeted had 37% more retweets (adjusted prevalence ratio [aPR] 1.37 [95% CI 1.06 to 1.78]). Tweets that raised concerns about vaccine price were twice as likely to be retweeted (aOR 2.29 [95% CI 1.36 to 3.84]) and if retweeted, had double the retweet count (aPR 2.05 [95% CI 1.27 to 3.29]) of tweets sharing personal experience. Conclusions: The #pneumonia tweets that both raised awareness and promoted interventions and those discussing vaccine price were more likely to engage users than tweets about personal experience. These results help health professionals craft WPD messages that will engage the audience.

Original languageEnglish
Pages (from-to)297-305
Number of pages9
JournalInternational Health
Volume11
Issue number4
DOIs
StatePublished - Jul 1 2019

Keywords

  • health communication
  • health marketing
  • machine learning
  • manual coding
  • social media

Fingerprint

Dive into the research topics of 'World Pneumonia Day 2011-2016: Twitter contents and retweets'. Together they form a unique fingerprint.

Cite this