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.
Nick Yee has an extensive research background in the psychology of virtual environments and online interaction. He’s worked with PARC’s PlayOn group and Sony Online Entertainment to examine large data sets of behavioral data from online games. At PARC, he’s also studied how people use and react to context-aware mobile applications.
At Stanford’s Virtual Human Interaction Lab, Nick conducted experiments in immersive virtual reality to explore digital self representation and social interaction. He is also well-known for the Daedalus Project, a long-running survey study of over 50,000 online gamers exploring demographic patterns, play motivations, and emergent social phenomena. His interest in online interaction began when a personality psychology professor in college asked students to create their own webpage (this was back in 1998) as a tool to understand identity projection online.
Nick received his Ph.D. in Communication from Stanford University. His work has been cited by the New York Times, CNN, the Discovery Channel, and Science, among other news outlets.
In his free time, he polishes rough amber on a lapidary machine.
Nic is a Senior Member of the Research Staff in the Computing Science Lab. He uses a combination of methods (including data mining and social network analysis) to study and design systems to better support collaboration in online spaces, with a recent focus on 3D virtual worlds and massively multiplayer online games. He conducted the largest and longest (to date) study of social dynamics in World of Warcraft, collecting and analyzing data on the interactions between more than 500,000 characters over 2 years.
Nic obtained his Ph.D. from the University of California, Berkeley. Outside of work, he enjoys sailing and restoring boats, especially older designs based on the CCA rule.
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