#Sleep_as_Android: Feasibility of Using Sleep Logs on Twitter for Sleep Studies
July 21, 2016 Β· Declared Dead Β· π IEEE International Conference on Healthcare Informatics
"No code URL or promise found in abstract"
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Authors
Fatema Akbar, Ingmar Weber
arXiv ID
1607.06359
Category
cs.HC: Human-Computer Interaction
Cross-listed
cs.CY
Citations
6
Venue
IEEE International Conference on Healthcare Informatics
Last Checked
4 months ago
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.
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