Clinical Age-Specific Seasonal Conjunctivitis Patterns and Their Online Detection in Twitter, Blog, Forum, and Comment Social Media Posts.

ABSTRACT:

Purpose

We sought to determine whether big data from social media might reveal seasonal trends of conjunctivitis, most forms of which are nonreportable.

Methods

Social media posts (from Twitter, and from online forums and blogs) were classified by age and by conjunctivitis type (allergic or infectious) using Boolean and machine learning methods. Based on spline smoothing, we estimated the circular mean occurrence time (a measure of central tendency for occurrence) and the circular variance (a measure of uniformity of occurrence throughout the year, providing an index of seasonality). Clinical records from a large tertiary care provider were analyzed in a similar way for comparison.

Results

Social media posts machine-coded as being related to infectious conjunctivitis

SUBMITTER: Deiner MS 

PROVIDER: S-EPMC5815847 | biostudies-literature | 2018 Feb

REPOSITORIES: biostudies-literature