Presentation at O'Reilly Strata Conference: http://strataconf.com/strata2011/public/schedule/detail/17009 Virtual worlds are a goldmine of untapped behavioral data with insights that can be applied to many online social systems, as well as to the physical world. But unlike the physical world (where it is obtrusive and cost-prohibitive to follow distributed users around with video cameras and sensors), virtual worlds come readily instrumented. Anything a user says or does – including how often and in what ways they interact with other users and objects in their virtual environment – can be tracked over an extended period of time. In this presentation, PARC social scientists will share findings and methods (e.g., customized scripts) they developed to extract behavioral data from online games. While we will use the example of World of Warcraft, a massively popular online multiplayer game that appeals to a broad demographic (and has an average user age of 30), our data collection/analysis methods have been applied to other virtual environments as well. More importantly, we will discuss how we converted and processed raw behavioral metrics into meaningful psychological variables that can be applied to a broad spectrum of business applications and segments. Other questions we will address include: What are some of the unique data collection challenges in virtual environments? What are the pitfalls and advantages of large-scale data sets, real-time data monitoring, and more? How can one extrapolate insights from low-incident events to broader samples or domains? Meanwhile, our other goals in this work (which is partially funded by the U.S. government) were to examine: whether behaviors in virtual worlds can be used to predict a user’s demographic and personality; which cues are most predictive; and how well can these variables predict real world behaviors? The process we developed and our findings can be used to create practical, actionable tools for automated segmentation, targeted marketing, and other business intelligence.

1. Meaningful Insights From Raw Metrics Virtual Worlds and Other Business Applications

3. World of Warcraft PARC |

9. From Analysis to Action: The Social Dashboard PARC | Tools to help scientists, game producers, and players better understand these communities Assess the social health of a community at a glance

10. From Analysis to Action: The Social Dashboard PARC | Tools to help scientists, game producers, and players better understand these communities Drill down to identify endangered groups

11. From Analysis to Action: The Social Dashboard PARC | Tools to help scientists, game producers, and players better understand these communities Observe the evolution of key players over time

14. Reliable, Large Scale In-Game Data Collection PARC | PlayOn 1.0 PlayOn 2.0 Coverage Entire population on 5 US WoW servers 100s of characters spread across 280 servers in US, TW, HK Infrastructure 5 old PCs 10 virtual machines per 2.26Ghz Quad Core Mac Pro Code Static scripts and configuration Data collection code dynamically generated at runtime Data Local CVS files Stateless VMs with central SQL database

21. Gender-Bending PARC |

22. Hugs PARC |

23. Role Preference PARC |

25. HotSpot Rules (Gender) PARC | Male Female Condition 1 Condition 2 Precision Recall % of Male Chars > 30% 94% 81% % of PvP Achs > 7% 81% 82% Sum Hugs < 41 80% 82% Condition 1 Condition 2 Condition 3 P R Male Chars = 0 % Profession Achs > 9% % Tank <= 37% 81% 57% % Male Chars <= 13% % Profession Achs > 9% % PvP Achs < 13% 80% 57%

30. From Vision to Reality PARC |