This paper is in the following e-collection/theme issue:

Research Letter (37) Natural Language Processing (693) Ontologies, Classifications, and Coding (239) Infodemiology and Infoveillance (1349) Medicine 2.0: Social Media, Open, Participatory, Collaborative Medicine (1641) Infoveillance, Infodemiology, Digital Disease Surveillance, Infodemic Management (1041)

Published on in Vol 25 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/40569, first published .
Pregex: Rule-Based Detection and Extraction of Twitter Data in Pregnancy

Pregex: Rule-Based Detection and Extraction of Twitter Data in Pregnancy

Pregex: Rule-Based Detection and Extraction of Twitter Data in Pregnancy

Authors of this article:

Ari Z Klein1 Author Orcid Image ;   Shriya Kunatharaju1 Author Orcid Image ;   Karen O'Connor1 Author Orcid Image ;   Graciela Gonzalez-Hernandez2 Author Orcid Image
Article Authors Cited by (5) Tweetations (10) Metrics

Journals

  1. Thakur N, Duggal Y, Liu Z. Analyzing Public Reactions, Perceptions, and Attitudes during the MPox Outbreak: Findings from Topic Modeling of Tweets. Computers 2023;12(10):191 View
  2. Thakur N. Sentiment Analysis and Text Analysis of the Public Discourse on Twitter about COVID-19 and MPox. Big Data and Cognitive Computing 2023;7(2):116 View
  3. Klein A, Gutiérrez Gómez J, Levine L, Gonzalez-Hernandez G. Using Longitudinal Twitter Data for Digital Epidemiology of Childhood Health Outcomes: An Annotated Data Set and Deep Neural Network Classifiers. Journal of Medical Internet Research 2024;26:e50652 View

Books/Policy Documents

  1. Thakur N, Cho H, Cheng H, Lee H. HCI International 2023 – Late Breaking Papers. View