Research based on social media data may help overcome these limitations, according to researchers from Boston Children's Hospital and Merck.
"We wanted to see if we could use new forms of online data, such as Twitter, to characterise the sleep disordered individual and possibly uncover new, previously-undescribed populations of patients suffering sleep problems," said John Brownstein who directs the hospital's Computational Epidemiology Group.

The research team used publically available anonymised data from Twitter to create a virtual cohort of 896 active Twitter users whose tweets contained sleep-related words (eg, "can't sleep," "insomnia"), or hashtags (eg, #cantsleep, #teamnosleep), or the names of common sleep aids or medications.
The researchers then figured out what a profile of a Twitter user with sleep issues - compared to a Twitter user without - looked like.
A Twitter user with sleep issues is likely to have been active on Twitter for a relatively long time; has fewer followers and follows fewer people; posts few tweets per day on average; more active on Twitter between 6:00 pm and 5:59 am; more active on Twitter on weekends and early weekdays; and more likely to post tweets with negative sentiment.



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