Objective: To understand the predominant topics of discussion, stance and associated language used on social media platforms relating to maternal vaccines in 15 countries over a six-month period.
Background: In 2019, the World Health Organisation prioritised vaccine hesitancy as a top ten global health threat and recognized the role of viral misinformation on social media as propagating vaccine hesitancy. Maternal vaccination offers the potential to improve maternal and child health, and to reduce the risk of severe morbidity and mortality in pregnancy. Understanding the topics of discussion, stance and language used around maternal vaccines on social media can inform public health bodies on how to combat vaccine misinformation and vaccine hesitancy.
Methods: Social media data was extracted (Twitter, forums, blogs and comments) for six months from 15 countries (Australia, Brazil, Canada, France, Germany, India, Italy, Korea, Mexico, Panama, South Africa, Spain, United Kingdom and United States). We used stance, discourse and topic analysis to provide insight into the most frequent and weighted keywords, hashtags and themes of conversation within and across countries.
Results: We exported a total of 19,192 social media posts in 16 languages obtained between 1st November 2018 and 30th April 2019. After screening all posts, 16,000 were included in analyses, while excluding retweets, 2,722 were annotated for sentiment. Main topics of discussion were the safety of the maternal influenza and pertussis vaccines. Discouraging posts were most common in Italy (44.9%), and the USA (30.8%).
Conclusion: The content and stance of maternal vaccination posts from November 2018 to April 2019 differed across countries, however specific topics of discussion were not limited to geographical location. These discussions included the promotion of vaccination, involvement of pregnant women in vaccine research, and the trust and transparency of institutions. Future research should examine the relationship between stance (promotional, neutral, ambiguous, discouraging) online and maternal vaccination uptake in the respective regions.
Keywords: Discourse analysis; Hashtags; Machine learning; Maternal vaccines; Sentiment analysis; Social media; Stance analysis; Vaccine acceptance; Vaccine confidence; Vaccine misinformation; Vaccine uptake.
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