ArticleInternational journal of epidemiology2023
Epicosm-a framework for linking online social media in epidemiological cohorts.
Article in International journal of epidemiology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
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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.
The trial behind it
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Who cites it
4 citing papers in PubMed.
- Active night-time tweeting is associated with meaningfully lower mental wellbeing in a UK birth cohort study.Scientific reports · 2025Article
- Factors that affect clinical youth engagement in digital mental health research: a qualitative sub-study nested within a prospective cohort study.BMC medical research methodology · 2025Observational
- Linking digital footprint data into longitudinal population studies.International journal of population data science · 2025Article
- Precision Prevention through Social Media: Report of Four Cases.Yearbook of medical informatics · 2024Article
Corrections and comments
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Authors and funding
10 authors.
Funding
Abstract
motivationSocial media represent an unrivalled opportunity for epidemiological cohorts to collect large amounts of high-resolution time course data on mental health. Equally, the high-quality data held by epidemiological cohorts could greatly benefit social media research as a source of ground truth for validating digital phenotyping algorithms. However, there is currently a lack of software for doing this in a secure and acceptable manner. We worked with cohort leaders and participants to co-design an open-source, robust and expandable software framework for gathering social media data in epidemiological cohorts. IMPLEMENTATION: Epicosm is implemented as a Python framework that is straightforward to deploy and run inside a cohort's data safe haven. GENERAL FEATURES: The software regularly gathers Tweets from a list of accounts and stores them in a database for linking to existing cohort data. AVAILABILITY: This open-source software is freely available at [https://dynamicgenetics.github.io/Epicosm/].
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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.