  The dynamics of many social, technological and economic phenomena are driven
by individual human actions, turning the quantitative understanding of human
behavior into a central question of modern science. Current models of human
dynamics, used from risk assessment to communications, assume that human
actions are randomly distributed in time and thus well approximated by Poisson
processes. In contrast, there is increasing evidence that the timing of many
human activities, ranging from communication to entertainment and work
patterns, follow non-Poisson statistics, characterized by bursts of rapidly
occurring events separated by long periods of inactivity. Here we show that the
bursty nature of human behavior is a consequence of a decision based queuing
process: when individuals execute tasks based on some perceived priority, the
timing of the tasks will be heavy tailed, most tasks being rapidly executed,
while a few experience very long waiting times. In contrast, priority blind
execution is well approximated by uniform interevent statistics. These findings
have important implications from resource management to service allocation in
both communications and retail.
