Boos Margarete, Pritz Johannes, Belz Michael
Institute for Psychology, University of Goettingen;
Courant Research Centre Evolution of Social Behavior, University of Goettingen.
J Vis Exp. 2019 Jan 19(143). doi: 10.3791/58719.
Collective human behavior such as group movement frequently shows surprising patterns and regularities, such as the emergence of leadership. Recent literature has revealed that these patterns, often visible at the global level of the group, are based on self-organized, individual behaviors that follow several simple local parameters. Understanding the dynamics of human collective behavior can help to improve coordination and leadership in group and crowd scenarios, such as identifying the ideal placement and number of emergency exits in buildings. In this article, we present the experimental paradigm HoneyComb, which can be used to systematically investigate conditions and effects of human collective behavior. This paradigm uses a computer-based multi-user platform, providing a setting that can be shaped and adapted to various types of research questions. Situational conditions (e.g., cost-benefit ratios for specific behavior, monetary incentives and resources, various degrees of uncertainty) can be set by experimenters, depending on the research question. Each participant's motions are recorded by the server as hexagonal coordinates with timestamps at an accuracy of 50 ms and with individual IDs. Thus, a metric can be defined on the playfield, and movement parameters (e.g., distances, velocity, clustering, etc.) of participants can be measured over time. Movement data can in turn be combined with non-computerized data from questionnaires garnered within the same experiment setup. The HoneyComb paradigm is paving the way for new types of human movement experiments. We demonstrate here that these experiments can render results with sufficient internal validity to meaningfully deepen our understanding of human collective behavior.
诸如群体运动之类的人类集体行为常常呈现出惊人的模式和规律，比如领导力的出现。最近的文献表明，这些通常在群体全局层面可见的模式，是基于遵循几个简单局部参数的自组织个体行为。理解人类集体行为的动态变化有助于改善群体和人群场景中的协调与领导能力，比如确定建筑物中理想的紧急出口位置和数量。在本文中，我们介绍了实验范式HoneyComb，它可用于系统地研究人类集体行为的条件和影响。该范式使用基于计算机的多用户平台，提供一个可以根据各种研究问题进行塑造和调整的环境。实验者可以根据研究问题设置情境条件（例如，特定行为的成本效益比、金钱激励和资源、不同程度的不确定性）。服务器会以50毫秒的精度和个体ID将每个参与者的动作记录为六边形坐标并带有时间戳。因此，可以在游戏场上定义一个度量标准，并且可以随时间测量参与者的运动参数（例如，距离、速度、聚类等）。运动数据又可以与在同一实验设置中通过问卷调查获得的非计算机化数据相结合。HoneyComb范式正在为新型人类运动实验铺平道路。我们在此证明，这些实验能够产生具有足够内部效度的结果，从而有意义地加深我们对人类集体行为的理解。
