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.