Assessing social media platform data access for automated early warning of public health threats.

Epidemic Intelligence aims to promptly detect and monitor health threats, but processing large volumes of information is time-consuming. Automated social media (SM) data collection can enhance this process. We reviewed 36 pre-selected SM (as of 1 June 2024), evaluating content relevance, data extrac...

Full description

Bibliographic Details
Published in:	European Journal of Public Health Vol. 36; no. 4; pp. 1 - 4
Main Authors:	Siling, Katja, Orchard, Francisco, Espinosa, Laura
Format:	tables/charts Journal Article
Published:	Oxford University Press / USA Aug2026
Online Access:	View this record in EBSCOhost

Description
Summary:	Epidemic Intelligence aims to promptly detect and monitor health threats, but processing large volumes of information is time-consuming. Automated social media (SM) data collection can enhance this process. We reviewed 36 pre-selected SM (as of 1 June 2024), evaluating content relevance, data extraction mechanisms, and compliance with terms of use and data protection policies to assess suitability for inclusion in an automated early warning system. Six SM (BlueSky, Mastodon, Tumblr, X, Reddit, and YouTube) met all criteria. Findings can inform considerations for building a multi-source automated data collection system to strengthen early warning in public health and provide a framework for reassessing platform suitability as SM ecosystems evolve.