Social media is being increasingly used for scientific research owing to the large user-base and a new example of this sort of social media aided research is the use of Twitter data to analyse insomnia and other 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 is a the first ever study that looks into the relationship between social media use and sleep issues and based on the findings, scientists say that the sentiments expressed in users’ tweets–gives preliminary hints that patients with sleep disorders may be a greater risk of psychosocial issues.
According to statistics, sleep disorders including insomnia affects a whopping 50-70 million people in US alone and according to experts, such disorders not only affect productivity, but also contribute to other health hazards such as diabetes, cardiovascular disease and even depression.
The study–led by Jared Hawkins, PhD; David McIver, PhD; and John Brownstein, PhD, of Boston Children’s Informatics Program and researchers at Merck–is the product of a Boston Children’s/Merck collaboration on social media and sleep announced in 2014.
There has been prior research on sleep disorders including insomnia, but owing to the resource and time intensive methods, there has been a long gap in between the data collection, analysis and reporting.
Researchers believe that social media data may help overcome these limitations. To support such research, Hawkins, McIver, Brownstein and their colleagues sought to develop a “digital phenotype,” or baseline profile of what a person suffering insomnia or other sleep disorders “looks” like on social media.
“Sleep deprivation and chronic sleep disorders are not well understood,” said Brownstein, who directs the hospital’s Computational Epidemiology Group. “We 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.”
For the research, scientists used used publically available anonymized data from Twitter including age, total number of tweets, followers, length of time on Twitter, number of favourite tweets, location and timezone among other things to create a virtual cohort of 896 active Twitter users whose tweets contained sleep-related words (e.g., “can’t sleep,” “insomnia”), or hashtags (e.g., #cantsleep, #teamnosleep), or the names of common sleep aids or medications. They then compared data from that cohort to those of a second group of 934 users who did not tweet using sleep-related terms.
One important thing that researchers kept note of was the time of day and average sentiment–positive, neutral, negative–of each user’s tweets.
Based on the analysis, profile of a Twitter user with sleep issues when compared to a Twitter user without any such disorder 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
- 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.
“These findings are preliminary and observational only, and need to be studied further,” Brownstein cautioned. “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 findings have been published in the Journal of Medical Internet Research.