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Using Longitudinal Twitter Data for Digital Epidemiology of Childhood Health Outcomes: An Annotated Data Set and Deep Neural Network Classifiers
oleh: Ari Z Klein, José Agustín Gutiérrez Gómez, Lisa D Levine, Graciela Gonzalez-Hernandez
| Format: | Article |
|---|---|
| Diterbitkan: | JMIR Publications 2024-03-01 |
Deskripsi
We manually annotated 9734 tweets that were posted by users who reported their pregnancy on Twitter, and used them to train, evaluate, and deploy deep neural network classifiers (F1-score=0.93) to detect tweets that report having a child with attention-deficit/hyperactivity disorder (678 users), autism spectrum disorders (1744 users), delayed speech (902 users), or asthma (1255 users), demonstrating the potential of Twitter as a complementary resource for assessing associations between pregnancy exposures and childhood health outcomes on a large scale.