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Epicosm -a framework for linking online social media in epidemiological cohorts

Tanner, Alastair R., Di Cara, Nina H., Maggio, Valerio, Thomas, Richard, Boyd, Andy, Sloan, Luke ORCID:, Al Baghal, Tarek, Macleod, John, Haworth, Claire M. A. and Davis, Oliver S. P. 2023. Epicosm -a framework for linking online social media in epidemiological cohorts. International Journal of Epidemiology 52 (3) , pp. 952-957. 10.1093/ije/dyad020

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Motivation Social 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 [].

Item Type: Article
Date Type: Publication
Status: Published
Schools: Social Sciences (Includes Criminology and Education)
Publisher: Oxford University Press
ISSN: 0300-5771
Funders: ESRC, MRC, EPSRC, Philip Leverhulme Prize
Date of First Compliant Deposit: 8 March 2023
Date of Acceptance: 16 February 2023
Last Modified: 13 Jul 2023 16:56

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