虚拟世界中人类多层次活动的时间间隔分布
Interevent time distributions of human multi-level activity in a virtual world
摘要：
研究人类在虚拟环境中的行为提供了非凡的机会，定量分析社会现象的准确性接近自然科学的水平。本文利用大型多人在线游戏《Pardus》连续1,238天的玩家活动记录，分析了玩家行为序列的动态特征。我们建立在以前的工作是相同类型的人类行为的时间结构进行了量化，并扩展提供不同类型的人类行为的经验理解。这种对多层次人类活动的研究可以看作是静态多元网络分析的动态对应。我们发现，在Pardus宇宙中的行动的intervent时间分布遵循高度非平凡的分布函数，从中我们提取的行动类型的具体特征“衰减常数”。我们讨论了事件间时间分布的特征，包括不同时间尺度上的周期性模式，突发动力学，以及不同时间尺度上的各种函数形式。我们评论的性别差异的球员在情绪行动，并发现，虽然男性和女性的行为相似时，执行一些积极的行动，女性略快于消极的行动。我们还观察到了对玩家年龄的影响：经验丰富的玩家通常会更快地做出决定，分别参与和终止敌意和友谊。
英文摘要：
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.
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