Collaborative Research: DHB Virtual Worlds: An Exploratorium for Theorizing and Modeling the Dynamics of Group Behavior

这个主要的跨学科研究工作将使用虚拟世界作为一个探索者，从理论上扩展和经验上模拟群体行为的动态。在这个过程中，它将开发新的计算技术来分析大规模的网络，这将在各种各样的领域具有适用性。政府和组织做出的最重要和最复杂的决定发生在群体背景下。在信息技术（IT）新发展的推动下，一个核心挑战是群体的性质及其运作方式发生了根本性的变化。今天，许多团体？在社会、政治和经济环境中，“原始”是从一个更大的原始关系网络中产生的临时的、灵活的、短暂的实体。在很短的时间内，这些小组完成了各种任务，然后解散，只是为了稍后以不同的配置重新组建。虽然人们日益认识到这些群体的社会经济后果，但我们对它们如何形成及其对效力的影响的了解严重有限。这个项目将通过发展一个反映当代群体概念的理论框架来解决这一限制。它提出了一种网络方法来建模重叠和不断变化的群体构成当代社会结构的生态系统。它认识到，从经验上测试这样一个模型会带来巨大的数据收集挑战。然而，对于研究团队来说，一个独特的资源是访问来自世界上最大的大型多人在线（MMO）游戏之一的所有行为痕迹（服务器日志），EverQuest 2，这特别适合于理论化和经验化群体行为的动态模型。mmo是由成千上万的玩家组成的，他们在任何时候都组成数千个小组来完成“任务”和“突袭”，这些任务涉及的各种活动与我们在现实生活中承担的任务类似。寻找信息或材料，制作、销售或购买产品和服务。除了数据收集的挑战之外，拟议研究企业的规模在揭示和分析这些虚拟世界中控制群体行为动态的复杂性方面也提出了重大的计算挑战。使用先进的计算应用程序和技术，该项目寻求捕获、推断和建模网络，以解释群体如何出现以及它们如何运作。具体来说，研究人员将使用时间演化图来模拟这样的网络，并开发可扩展的算法来计算它们上的群体行为指标。将这些复杂的、不断变化的个人和网络行为与传统形式的分析联系起来，在范围和复杂性上都是一种新的跨学科挑战。这个项目将扩展我们关于群体如何在更大的群体、个人和组织的生态系统中形成和运作的知识。从计算的角度来看，对虚拟世界生成的日志的分析提出了新的挑战。这项跨学科的研究将产生新的(1)虚拟世界建模的信息模型，(2)数据访问和分析的数据结构和算法技术，以及(3)计算效率的技术。本研究中开发的知识和工具将使研究人员更充分地了解当代社会中特设群体的出现和表现，并使实践者更有效地培养。它还将为其他学科提供新的计算和统计建模方法和工具，这将对其他学科领域的未来研究产生相当积极的影响。拟议研究的发现和成果将立即推广到与团体（不仅仅是mmo或虚拟世界）、社交网络和在线游戏相关的培训和教育中。

This major inter-disciplinary research effort will use virtual worlds as an exploratorium to theoretically extend and empirically model the dynamics of group behavior. In the process it will develop novel computational techniques for analyzing large-scale networks, which will have applicability across a wide variety of domains.The most important and complex decisions made by governments and organizations occur in group contexts. A central challenge, spurred by new developments in information technologies (IT), is that the nature of groups and how they operate has changed radically. Today, many groups ? in social, political, and economic contexts - are ad hoc, agile, transient entities that emerge from a larger primordial network of relationships. For a short time, these groups accomplish a variety of tasks, and then they dissolve, only to be reconstituted later with a different configuration. While there is growing awareness of the socio-economic consequences of these groups, our understanding of how they form and their impact on effectiveness is severely limited.This project will address this limitation by developing a theoretical framework that reflects the contemporary conceptualizations of groups. It proposes a network approach to modeling the eco-system of overlapping and constantly changing groups that constitute the fabric of contemporary society. It recognizes that empirically testing such a model poses formidable data collection challenges. However, a unique resource available to the research team is access to all behavioral traces (server logs) from one of the world''s largest Massively Multiplayer Online (MMO) games, EverQuest 2, which is particularly well-suited to theorize and empirically model the dynamics of group behavior. MMOs comprise tens of thousands of players who are at any one point in time coalescing in thousands of groups to accomplish ""quests"" and ""raids"" that involve a variety of activities similar to tasks we undertake in real life ? finding information or materials, making, selling or buying products and services. Beyond the data collection challenge, the scale of the proposed research enterprise also poses significant computational challenges in uncovering and analyzing the complexities that govern the dynamics of group behavior in these virtual worlds. Using advanced computing applications and technologies, this project seeks to capture, infer, and model the networks that explain how groups emerge and how they function. Specifically, the researchers will use temporally evolving graphs to model such networks, and develop scalable algorithms to compute metrics of group behavior on them. Tying these complex and shifting individual and networked behaviors to traditional forms of analyses represents a novel interdisciplinary challenge in both scope and complexity.The project will expand our knowledge of how groups form and operate in larger ecosystems of groups, individuals, and organizations. The analysis of logs generated from Virtual Worlds poses novel challenges from a computational perspective. This interdisciplinary investigation will result in new (1) information models for modeling the Virtual World, (2) data structuring and algorithmic techniques for data access and analysis, and (3) techniques for computational efficiency. The knowledge and tools developed in this research will allow researchers to understand more fully, and practitioners to cultivate more effectively, the emergence and performance of ad hoc groups in contemporary society. It will also provide other disciplines with new computational and statistical modeling methodologies and tools, which should have considerable positive implications for future research in other disciplinary areas. The findings and deliverables of the proposed research will be immediately generalizable to training and education related to groups (beyond just MMOs or Virtual Worlds), social networks, and online games.