ArticleEuropean journal of public health2026
Assessing social media platform data access for automated early warning of public health threats.
Article in European journal of public health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Authors and funding
3 authors.
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Abstract
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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.