#Sleep_as_Android: Feasibility of Using Sleep Logs on Twitter for Sleep Studies
This work addresses the challenge of obtaining quantitative sleep data for researchers by leveraging social media, though it is incremental as it builds on existing methods for data collection.
The study tackled the problem of using social media for sleep research by proposing and validating an approach to collect and analyze sleep logs from a mobile app, showing that collected data aligns with other sources and higher social media activity correlates with lower sleep duration and quality.
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.