Insomnia? Here's how your tweets may show it!

A new study has suggested that Twitter data may help shed light on sleep disorders.

Washington: A new study has suggested that Twitter data may help shed light on sleep disorders.

Researchers from Boston Children's Hospital and Merck have built the beginnings of "digital phenotype" of insomnia and other sleep disorders based on data from Twitter.

This study is one of the first to look at relationships between social media use and sleep issues, and based on assessments the sentiments expressed in users' tweets, gives preliminary hints that patients with sleep disorders may be a greater risk of psychosocial issues.

Sleep deprivation and chronic sleep disorders are not well understood, said one of the study leaders John Brownstein, adding that they wanted to see if we could use new forms of online data, such as Twitter, to characterize the sleep disordered individual and possibly uncover new, previously-undescribed populations of patients suffering sleep problems.

The resulting profile of a Twitter user with sleep issues compared to a Twitter user without looked like this: "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.

Taken together, the data suggest that Twitter users suffering from a sleep disorder are less active on Twitter on average but tweet more during traditional sleeping hours. The increase in negative sentiment in their tweets suggests that sleep-disordered users could be at an increased risk for psychosocial issues.

Brownstein cautioned that these findings are preliminary and observational only, and need to be studied further, but they suggest that social media can be a useful addition to our toolkit for studying the patient experience and behavioral epidemiology of sleep disorders.

The study is published in the Journal of Medical Internet Research.

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