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Accepted for/Published in: JMIR Public Health and Surveillance

Date Submitted: Aug 10, 2021
Date Accepted: Oct 13, 2021
Date Submitted to PubMed: Dec 6, 2021

The final, peer-reviewed published version of this preprint can be found here:

Factors Driving the Popularity and Virality of COVID-19 Vaccine Discourse on Twitter: Text Mining and Data Visualization Study

Zhang J(, Wang Y(, Shi M, Wang X

Factors Driving the Popularity and Virality of COVID-19 Vaccine Discourse on Twitter: Text Mining and Data Visualization Study

JMIR Public Health Surveill 2021;7(12):e32814

DOI: 10.2196/32814

PMID: 34665761

PMCID: 8647971

What drives popularity and virality of COVID-19 vaccine discourse on Twitter: Insights from text mining and network visualization

  • Jueman (Mandy) Zhang; 
  • Yi (Jasmine) Wang; 
  • Molu Shi; 
  • Xiuli Wang

ABSTRACT

Background:

COVID-19 vaccination is considered as a critical prevention measure to help end the pandemic. Social media such as Twitter has played an important role in public discussion about COVID-19 vaccines.

Objective:

This study intended to investigate drivers of the popularity and virality of tweets about COVID-19 vaccines using machine-based text mining techniques. It also examined the topic communities of the most liked and most retweeted tweets using network analysis and visualization.

Methods:

We collected US-based English-language public tweets about COVID-19 vaccines from January 1, 2020 to April 30, 2021 (n=501,531). Topic modeling and sentiment analysis were used to identify latent topics and valence, which together with auto-extracted information about media presence, linguistic features, and account verification were used in regression models to predict likes and retweets. Among the 2,500 most liked tweets and most retweeted tweets respectively, network analysis and visualization were used to detect topic communities and present the relationship between the topics and the tweets.

Results:

Topic modeling yielded 12 topics. The regression analyses showed that eight topics predicted likes and seven topics predicted retweets, among which, the topic of vaccine efficacy and rollout and that of vaccine development and people’s views had relatively larger effects. Network analysis and visualization revealed that the 2,500 most liked and most retweeted retweets were clustered around the topics of vaccine access, vaccine efficacy and rollout, vaccine development and people’s views, and vaccination status. The overall valence of tweets was positive. Positive valence increased likes, but valence did not affect retweets. Media presence and account verification increased likes and retweets. Linguistic features had mixed effects on likes and retweets.

Conclusions:

The study revealed the public interest in and demand for information about COVID-19 vaccine access, efficacy and rollout, as well as development and people’s views. These topics, along with the use of media and verified accounts, could enhance the popularity and virality of tweets. Vaccine campaigns can use these strategies to make more effective content for Twitter. Clinical Trial: NA


 Citation

Please cite as:

Zhang J(, Wang Y(, Shi M, Wang X

Factors Driving the Popularity and Virality of COVID-19 Vaccine Discourse on Twitter: Text Mining and Data Visualization Study

JMIR Public Health Surveill 2021;7(12):e32814

DOI: 10.2196/32814

PMID: 34665761

PMCID: 8647971

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