#Sleep_as_Android: Feasibility of Using Sleep Logs on Twitter for Sleep Studies

TL;DR

This paper explores the feasibility of using sleep logs shared on Twitter, combined with social media activity, to conduct sleep studies, validating the approach with data from a sleep-tracking app and social media.

Contribution

It introduces a novel method of collecting and analyzing sleep logs from a mobile app and social media, validating its alignment with traditional sleep data sources.

Findings

Sleep data from social media aligns with other sleep measurement sources.

Higher social media activity correlates with reduced sleep duration.

Combining social media and sleep data offers insights into sleep patterns.

Abstract

Social media enjoys a growing popularity as a platform to seek and share personal health information. For sleep studies using data from social media, most researchers focused on inferring sleep-related artifacts from self-reported anecdotal pointers to sleep patterns or issues such as insomnia. The data shared by "quantified-selfers" on social media presents an opportunity to study more quantitative and objective measures of sleep. We propose and validate the approach of collecting and analyzing sleep logs that are generated and shared through a sleep-tracking mobile application. We highlight the value of this data by combining it with users' social media data. The results provide a validation of using social media for sleep studies as the collected sleep data is aligned with sleep data from other sources. The results of combining social media data with sleep data provide preliminary evidence that higher social media activity is associated with lower sleep duration and quality.