Collaborative Research: Instrumenting Behaviors and Attitudes in Virtual Worlds

这个项目是一个开拓性的努力，收集数据的大型多人在线游戏玩家，他们的行动，态度，社交网络，和经济活动。 人们越来越多地在虚拟世界中进行他们生活的主要部分：大量用户能够聚集，互动，游戏和社交的在线空间。这些世界中的大多数都是作为竞争性游戏而构建的，并被称为大型多人在线游戏（MMO）。最好的估计表明，超过500万北美人现在在这些世界上互动，全球超过2000万。然而，尽管对虚拟世界的认真研究已经开始，但由于缺乏系统的数据，它受到了阻碍。没有研究项目进行了代表性的样本，访问服务器端数据，或游戏管理员的合作。然而，该项目已获得一家大型游戏开发商的合作，该开发商已同意发布其游戏内数据，并帮助协调其玩家的调查工具。由此产生的数据集将是第一个全面的虚拟世界行为研究，并将包含一个罕见的结合两个不引人注目的行为数据与标准的态度，人口和心理的措施，这个数据集必须妥善收集，清理和组织，以方便广泛的研究人员访问。因此，最初的工作将涉及编程创新，清理和托管任务，以及为几个社会科学测试创建新算法。首先测试的三个领域将是社交网络、社会资本和经济活动。在每个领域，数据集都将成为以以前不可能的方式检验理论的试验平台，同时也提供了与处理大规模综合数据集有关的几个编程和分析挑战。例如，使用多理论多水平（MTML）模型测试的社交网络通常很小，因为很难收集关于群体的完整数据集，但目前的项目将提供数千个完整的群体，规模从2到2,000不等，在16个月的时间窗口内提供完整的行为数据。为了研究网络世界的社会影响，这些数据提供了对网络巴尔干化假设、新媒体隔离假设和虚拟社区探索的检验。该数据集还提供了在经济分析中从未做过的事情：生成整个经济的时间序列。大量的数据将需要建立指数、新的度量标准和新的解释方法。这个项目在社会科学中没有先例，既因为虚拟世界还没有被系统地研究，也因为它将态度数据与以前无法达到的不引人注目的行为数据相结合。该项目允许方法的突破以及创新的理论测试。这项研究将需要创造新的技术，桥接计算机科学和社会科学的领域。这些新方法对于未来的科学研究、改进游戏本身以及开发虚拟世界的教育潜力都是有价值的。

This project is a pioneering effort to collect data about Massively Multiplayer Online game players, their actions, attitudes, social networks, and economic activities. People increasingly conduct major parts of their lives in virtual worlds: online spaces where large numbers of users are able to congregate, interact, play, and socialize. Most of these worlds are built as competitive games, and are termed Massively Multiplayer Online games (MMOs). Best estimates indicate in excess of five million North Americans now interact in these worlds, with more than 20 million worldwide. Yet while the serious study of virtual worlds has begun in earnest, it is hamstrung by the absence of systematic data. No research project has been conducted with a representative sample, access to server-side data, or the cooperation of game administrators. However, this project has secured the cooperation of a large game developer, which has agreed to release its in-game data as well as help coordinate a survey instrument of its players. The resulting data set will thus be the first comprehensive study of virtual world behaviors, and will contain a rare combination of both unobtrusive behavioral data with standard attitudinal, demographic and psychographic measures.This data set must be properly collected, cleaned and organized in order to facilitate access by a wide range of researchers. Thus the initial effort will involve programming innovations, cleaning and hosting tasks, as well as the creation of new algorithms for several social science tests. The first three areas to be tested will be social networks, social capital, and economic activity. In each area, the dataset will be a testbed for examining theories in ways that were previously impossible, while also offering several programming and analysis challenges relating to dealing with a massive and comprehensive dataset. For example, social networks tested with multi-theoretical multilevel (MTML) models have generally been small due to the difficulty of collecting complete datasets on groups, yet the current project will offer thousands of complete groups of sizes ranging from two to 2,000, with complete behavioral data over a 16-month time window. For research into the social implications of online worlds, the data offer tests of the cyberbalkanization hypothesis, new media isolation hypotheses and explorations of virtual communities. The dataset also offers the ability to do something never yet done in economic analysis: generate a time series of an entire economy. The wealth of data will require the creation of indices, new metrics and new ways of interpretation.This project has no precedent in social science, both because virtual worlds have not yet been studied systematically, and because it combines attitudinal data with previously unattainable levels of unobtrusive behavioral data. The project allows for both methodological ground breaking as well as innovative theory testing. The research will require the creation of new techniques bridging the domains of both computer science and social science. These new methods will be valuable for future scientific research, for improving the games themselves, and for exploiting the educational potential of virtual worlds.