Social media mining for birth defects research: A rule-based, bootstrapping approach to collecting data for rare health-related events on Twitter.

ABSTRACT:

Background

Although birth defects are the leading cause of infant mortality in the United States, methods for observing human pregnancies with birth defect outcomes are limited.

Objective

The primary objectives of this study were (i) to assess whether rare health-related events-in this case, birth defects-are reported on social media, (ii) to design and deploy a natural language processing (NLP) approach for collecting such sparse data from social media, and (iii) to utilize the collected data to discover a cohort of women whose pregnancies with birth defect outcomes could be observed on social media for epidemiological analysis.

Methods

To assess whether birth defects are mentioned on social media, we mined 432 million tweets posted by 112,647 users who were automati

SUBMITTER: Klein AZ 

PROVIDER: S-EPMC6295660 | biostudies-literature | 2018 Nov

REPOSITORIES: biostudies-literature