Social virtual worlds such as Second Life (SL) are digital representations of the real world where human-controlled avatars evolve and interact through social activities. Understanding the characteristics of virtual worlds can be extremely valuable in order to optimize their design. In this paper, we perform an extensive analysis of SL. We exploit standard avatar capabilities to monitor the virtual world, and we emulate avatar behaviors in order to evaluate user experience. We make several surprising observations. We find that 30% of the regions are never visited during the six-day monitoring period, whereas less than 1% of the regions have large peak populations. Moreover, the vast majority of regions are static, i.e., objects are seldom created or destroyed. Interestingly, we show that avatars interact similarly to humans in real life, gathering in small groups of 2–10 avatars. We also show that user experience is poor. Most of the time, avatars have an incorrect view of their neighbor avatars, and inconsistency can last several seconds, impacting interactivity among avatars.