Abstract
Text analysis has been used by scholars to research attitudes toward vaccination and is particularly timely due to the rise of medical misinformation via social media. This study uses a sample of 9581 vaccine-related tweets in the period 1 January 2019 to 5 April 2019. The time period is of the essence because during this time, a measles outbreak was prevalent throughout the United States and a public debate was raging. Sentiment analysis is applied to the sample, clustering the data into topics using the term frequency–inverse document frequency (TF-IDF) technique. The analyses suggest that most (about 77%) of the tweets focused on the search for new/better vaccines for diseases such as the Ebola virus, human papillomavirus (HPV), and the flu. Of the remainder, about half concerned the recent measles outbreak in the United States, and about half were part of ongoing debates between supporters and opponents of vaccination against measles in particular. While these numbers currently suggest a relatively small role for vaccine misinformation, the concept of herd immunity puts that role in context. Nevertheless, going forward, health experts should consider the potential for the increasing spread of falsehoods that may get firmly entrenched in the public mind.
Highlights
In this research, we use Twitter data to discover and describe public sentiment regarding vaccination
While we focused on tweets related to vaccines—and not necessarily to measles-related vaccines—it so happened that since the timeframe of our research coincided with the measles outbreak in the United States, most of the tweets naturally related to it
We first lay the foundation for our research with a discussion on the incidence of measles and the status of vaccination for the same; we cover the general topic of sentiment towards vaccination; we describe the dissemination of such sentiments through the channel of social media, highlighting the relevant paradox of information and misinformation; and we outline the potential and appropriateness of sentiment analysis as a technique for our research objective of analyzing public perception in healthcare
Summary
We use Twitter data to discover and describe public sentiment regarding vaccination This is timely since there was a large measles outbreak in the United States and other parts of the world in 2019 [1,2,3]. There are various social media outlets (e.g., Twitter, blogs, Facebook, Snapchat, etc.) for the public to discuss and disseminate their opinions and experiences. Along these lines, we selected a corpus of text related to vaccine-related comments on Twitter, as a representative social media channel. We first lay the foundation for our research with a discussion on the incidence of measles and the status of vaccination for the same; we cover the general topic of sentiment towards vaccination; we describe the dissemination of such sentiments through the channel of social media, highlighting the relevant paradox of information and misinformation; and we outline the potential and appropriateness of sentiment analysis as a technique for our research objective of analyzing public perception in healthcare
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