JMIR Publications

ABSTRACT

Background:

Understanding public discourse about a COVID-19 vaccine in the early phase of the COVID-19 pandemic may provide key insights concerning vaccine acceptance or hesitancy. However, few studies have investigated the communicative patterns in which Twitter users participate discursively in vaccine discussions.

Objective:

This study aims to investigate 1) the major themes that emerged from public conversation on Twitter concerning vaccines for COVID-19, 2) the topics that were emphasized in tweets with either positive or negative sentiment toward a COVID-19 vaccine, and 3) the type of online accounts in which tweets with either positive or negative sentiment were more likely to circulate.

Methods:

We randomly extracted a total of 349,979 COVID-19 vaccine-related tweets from the initial four-month period of pandemic planning and initial lockdowns (between March 1 and June 30, 2020). Out of 64,216 unique tweets, a total of 23,133 (36.03%) tweets were classified as positive and 14,051 (21.88%) as negative toward a COVID-19 vaccine using the Bidirectional Encoder Representations from Transformers (BERT) machine learning algorithm. We conducted Structural Topic Modeling (STM) and Network Analysis (NA) to reveal the distinct thematic structure and connection patterns that characterize positive and negative discourse toward a COVID-19 vaccine on Twitter.

Results:

Our STM analysis revealed the most prominent topic that emerged from the U.S. public discussion on Twitter of a COVID-19 vaccine was “other infectious diseases”, followed by “vaccine safety concerns”, and “conspiracy theory.” Comparing the thematic focus of positive and negative discourses, while the positive discourse demonstrated a broad range of themes such as “vaccine development”, “vaccine effectiveness”, and “safety test”, negative discourse was more narrowly focused on topics such as “conspiracy theory” and “safety concerns.” Beyond topical differences, positive discourse was more likely to interact with verified sources such as scientists/medical sources and the media/journalists, whereas negative discourse tended to interact with politicians, online influencers, and suspended accounts.

Conclusions:

Positive and negative discourse was not only structured around distinct topics but also circulated within different networks. Our findings suggest that public health communicators need to address specific topics of public concern in varying information hubs to deliver more tailored messages based on audience segmentation, potentially increasing COVID-19 vaccine uptake.