Article

Denoising Longitudinal Social Media for Pandemic Monitoring

2024-06-30

Abstract excerpt

<h4>Objective</h4> Current studies leveraging social media data for disease monitoring face challenges like noisy colloquial language and insufficient tracking of user disease progression in longitudinal data settings. This study aims to develop a pipeline for collecting, cleaning, and analyzing large-scale longitudinal social media data for disease monitoring, with a focus on COVID-19 pandemic. <h4>Materials and...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: e377118f-f70a-50ea-bc4d-0991e6aebc68
DOI: 10.1101/2024.06.29.24309690

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Denoising Longitudinal Social Media for Pandemic MonitoringDOI 10.1101/2024.06.29.24309690Read

Characterization of long-term patient-reported symptoms of COVID-19: an analysis of social media dataSemantic proximity Read

Using Social Media to Help Understand Long COVID Patient Reported Health Outcomes: A Natural Language Processing ApproachSemantic proximity Read

Trend and co-occurrence network study of symptoms through social media: an example of COVID-19Semantic proximity Read

Social media can predict the COVID-19 epidemic in ChinaSemantic proximity Read

Natural Language Processing for Improved COVID-19 Characterization: Evidence from More than 350,000 Patients in a Large Integrated Health Care SystemSemantic proximity Read

Moving Biosurveillance Beyond Coded Data: AI for Symptom Detection from Physician NotesSemantic proximity Read

Consistent Comparison of Symptom-based Methods for COVID-19 Infection DetectionSemantic proximity Read

Long COVID symptoms from Reddit: Characterizing post-COVID syndrome from patient reportsSemantic proximity Read

Integrating Zero-Shot Classification to Advance Long COVID Literature: A Systematic Social Media–Centered ReviewSemantic proximity Read

A Longitudinal and Geospatial Analysis of COVID-19 Tweets During the Early Outbreak Period in the United StatesSemantic proximity Read

Enhancing Pandemic Prediction: A Deep Learning Approach Using Transformer Neural Networks and Multi-Source Data Fusion for Infectious Disease ForecastingSemantic proximity Read

Analysis on Action Tracking Reports of COVID-19 Informs Control Strategies and Vaccine Delivery in Post-Pandemic EraSemantic proximity Read