Leveraging machine learning-based approaches to assess human papillomavirus vaccination sentiment trends with Twitter data.

ABSTRACT:

Background

As one of the serious public health issues, vaccination refusal has been attracting more and more attention, especially for newly approved human papillomavirus (HPV) vaccines. Understanding public opinion towards HPV vaccines, especially concerns on social media, is of significant importance for HPV vaccination promotion.

Methods

In this study, we leveraged a hierarchical machine learning based sentiment analysis system to extract public opinions towards HPV vaccines from Twitter. English tweets containing HPV vaccines-related keywords were collected from November 2, 2015 to March 28, 2016. Manual annotation was done to evaluate the performance of the system on the unannotated tweets corpus. Followed time series analysis was applied to this corpus to track the tre

SUBMITTER: Du J 

PROVIDER: S-EPMC5506590 | biostudies-literature | 2017 Jul

REPOSITORIES: biostudies-literature