Using Twitter to Measure Public Discussion of Diseases: A Case Study.

ABSTRACT:

Background

Twitter is increasingly used to estimate disease prevalence, but such measurements can be biased, due to both biased sampling and inherent ambiguity of natural language.

Objective

We characterized the extent of these biases and how they vary with disease.

Methods

We correlated self-reported prevalence rates for 22 diseases from Experian's Simmons National Consumer Study (n=12,305) with the number of times these diseases were mentioned on Twitter during the same period (2012). We also identified and corrected for two types of bias present in Twitter data: (1) demographic variance between US Twitter users and the general US population; and (2) natural language ambiguity, which creates the possibility that mention of a disease name may not actually refer to th

SUBMITTER: Weeg C 

PROVIDER: S-EPMC4763717 | biostudies-literature | 2015 Jun

REPOSITORIES: biostudies-literature