  Using mobile phone records and information theory measures, our daily lives
have been recently shown to follow strict statistical regularities, and our
movement patterns are to a large extent predictable. Here, we apply entropy and
predictability measures to two data sets of the behavioral actions and the
mobility of a large number of players in the virtual universe of a massive
multiplayer online game. We find that movements in virtual human lives follow
the same high levels of predictability as offline mobility, where future
movements can to some extent be predicted well if the temporal correlations of
visited places are accounted for. Time series of behavioral actions show
similar high levels of predictability, even when temporal correlations are
neglected. Entropy conditional on specific behavioral actions reveals that in
terms of predictability negative behavior has a wider variety than positive
actions. The actions which contain information to best predict an individual's
subsequent action are negative, such as attacks or enemy markings, while
positive actions of friendship marking, trade and communication contain the
least amount of predictive information. These observations show that predicting
behavioral actions requires less information than predicting the mobility
patterns of humans for which the additional knowledge of past visited locations
is crucial, and that the type and sign of a social relation has an essential
impact on the ability to determine future behavior.
