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...

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Detalles Bibliográficos
Publicado en:European Journal of Public Health Vol. 36; no. 4; pp. 1 - 4
Autores principales: Siling, Katja, Orchard, Francisco, Espinosa, Laura
Formato: tables/charts Journal Article
Publicado: Oxford University Press / USA Aug2026
Acceso en línea:Ver este registro en EBSCOhost
Descripción
Sumario: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.