Interevent time distributions of human multi-level activity in a virtual world

TL;DR

This study analyzes human activity patterns in a virtual world, revealing complex interevent time distributions, behavioral differences based on gender and experience, and extending understanding of multi-level social dynamics through empirical data.

Contribution

It provides the first detailed empirical analysis of multi-level human activity patterns in a virtual environment, highlighting non-trivial interevent time distributions and behavioral differences.

Findings

Interevent time distributions are highly non-trivial and action-specific.

Gender differences exist in response times for emotional actions.

Player experience correlates with faster decision-making in social interactions.

Abstract

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.