YeZzzs Does it: Studying Sleep and Emotion using the Digital Rest-Activity Rhythms of Kanye West’s Tweets

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Abstract

One of the greatest challenges faced by the field of precision medicine is the identification of biomarkers capable of detecting clinically meaningful change at the individual level, not just amongst large-scale population studies. To this end, the evermore present social mediaverse provides unparalleled access to ecologically-valid databases of digital-biomarkers, that could be leveraged with single-user precision to support mental health care by monitoring use-patterns and emotional state. Despite this potential, investigation into how social-media use can be used to study sleep-wake behaviors has been remarkably scant, in part due to a lack of established methods to detect and estimate sleep using social-media activity. We present here a new approach to using social media-based data to track both sleep and mood, with potential applications to mental health monitoring and prevention. Amongst demonstrating proof of concept, we also provide an ethical and theoretical framework of how to proceed amongst this sensitive but potentially highly fruitful field.
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Abstract One of the greatest challenges faced by the field of precision medicine is the identification of biomarkers capable of detecting clinically meaningful change at the individual level, not just amongst large-scale population studies. To this end, the evermore present social mediaverse provides unparalleled access to ecologically-valid databases of digital-biomarkers, that could be leveraged with single-user precision to support mental health care by monitoring use-patterns and emotional state. Despite this potential, investigation into how social-media use can be used to study sleep-wake behaviors has been remarkably scant, in part due to a lack of established methods to detect and estimate sleep using social-media activity. We present here a new approach to using social media-based data to track both sleep and mood, with potential applications to mental health monitoring and prevention. Amongst demonstrating proof of concept, we also provide an ethical and theoretical framework of how to proceed amongst this sensitive but potentially highly fruitful field. Competing Interest Statement The authors have declared no competing interest. Funding Statement This study did not receive any funding Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes Data Availability data is derived from publically available social media data

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last seen: 2026-05-20T01:45:00.602351+00:00