  Studying human behaviour in virtual environments provides extraordinary
opportunities for a quantitative analysis of social phenomena with levels of
accuracy that approach those of the natural sciences. In this paper we use
records of player activities in the massive multiplayer online game Pardus over
1,238 consecutive days, and analyze dynamical features of sequences of actions
of players. We build on previous work were temporal structures of human actions
of the same type were quantified, and extend provide an empirical understanding
of human actions of different types. This study of multi-level human activity
can be seen as a dynamic counterpart of static multiplex network analysis. We
show that the interevent time distributions of actions in the Pardus universe
follow highly non-trivial distribution functions, from which we extract
action-type specific characteristic "decay constants". We discuss
characteristic features of interevent time distributions, including periodic
patterns on different time scales, bursty dynamics, and various functional
forms on different time scales. We comment on gender differences of players in
emotional actions, and find that while male and female act similarly when
performing some positive actions, females are slightly faster for negative
actions. We also observe effects on the age of players: more experienced
players are generally faster in making decisions about engaging and terminating
in enmity and friendship, respectively.
