Characterizing Twitter Discussions About HPV Vaccines Using Topic Modeling and Community Detection.

ABSTRACT:

Background

In public health surveillance, measuring how information enters and spreads through online communities may help us understand geographical variation in decision making associated with poor health outcomes.

Objective

Our aim was to evaluate the use of community structure and topic modeling methods as a process for characterizing the clustering of opinions about human papillomavirus (HPV) vaccines on Twitter.

Methods

The study examined Twitter posts (tweets) collected between October 2013 and October 2015 about HPV vaccines. We tested Latent Dirichlet Allocation and Dirichlet Multinomial Mixture (DMM) models for inferring topics associated with tweets, and community agglomeration (Louvain) and the encoding of random walks (Infomap) methods to detect community

SUBMITTER: Surian D 

PROVIDER: S-EPMC5020315 | biostudies-literature | 2016 Aug

REPOSITORIES: biostudies-literature