Categorizing Vaccine Confidence With a Transformer-Based Machine Learning Model: Analysis of Nuances of Vaccine Sentiment in Twitter Discourse.

ABSTRACT:

Background

Social media has become an established platform for individuals to discuss and debate various subjects, including vaccination. With growing conversations on the web and less than desired maternal vaccination uptake rates, these conversations could provide useful insights to inform future interventions. However, owing to the volume of web-based posts, manual annotation and analysis are difficult and time consuming. Automated processes for this type of analysis, such as natural language processing, have faced challenges in extracting complex stances such as attitudes toward vaccination from large amounts of text.

Objective

The aim of this study is to build upon recent advances in transposer-based machine learning methods and test whether transformer-based machine le

SUBMITTER: Kummervold PE 

PROVIDER: S-EPMC8538052 | biostudies-literature | 2021 Oct

REPOSITORIES: biostudies-literature