  The dynamics of a wide range of real systems, from email patterns to
earthquakes, display a bursty, intermittent nature, characterized by short
timeframes of intensive activity followed by long times of no or reduced
activity. The understanding of the origin of such bursty patterns is hindered
by the lack of tools to compare different systems using a common framework. We
introduce two measures to distinguish the mechanisms responsible for the bursty
nature of real signals, changes in the interevent times and memory. We find
that while the burstiness of natural phenomena is rooted in both the interevent
time distribution and memory, for human dynamics memory is weak, and the bursty
character is due to changes in the interevent time distribution. Finally, we
show that current models lack in their ability to reproduce the activity
pattern observed in real systems, opening up new avenues for future work.
