Measuring Social Jetlag in Twitter Data

Social constraints have replaced the natural cycle of light and darkness as the main determinant of wakeup and activity times for many people. In this paper we show how Twitter activity can be used as a source of large-scale, naturally occurring data for the study of circadian rhythm in humans. Our year-long initial study is based on almost 1.5 million observations by over 200,000 users. The progression of the onset of Twitter activity times on free days in the course of the year is consistent with previous survey-based research on wake times. We show that the difference in wake-up time (implicating lack of sleep) on weekdays compared to Sundays is between 1 hour and over 2 hours depending on the time of year. The data also supports the assertion that Daylight Saving Time greatly disrupts the easing of social jetlag in the Spring transition.