Department of Network and Data Science, Central European University, Budapest, 1051, Hungary.
Laboratory for Networks, Innovation and Technology, Corvinus University, Budapest, 1093, Hungary.
Sci Rep. 2022 Jun 22;12(1):10498. doi: 10.1038/s41598-022-13929-0.
From sport and science production to everyday life, higher-level pursuits demand collaboration. Despite an increase in the number of data-driven studies on human behavior, the social dynamics of collaborative problem solving are still largely unexplored with network science and other computational and quantitative tools. Here we introduce escape rooms as a non-interventional and minimally biased social laboratory, which allows us to capture at a high resolution real-time communications in small project teams. Our analysis portrays a nuanced picture of different dimensions of social dynamics. We reveal how socio-demographic characteristics impact problem solving and the importance of prior relationships for enhanced interactions. We extract key conversation rules from motif analysis and discuss turn-usurping gendered behavior, a phenomenon particularly strong in male-dominated teams. We investigate the temporal evolution of signed and group interactions, finding that a minimum level of tense communication might be beneficial for collective problem solving, and revealing differences in the behavior of successful and failed teams. Our work unveils the innovative potential of escape rooms to study teams in their complexity, contributing to a deeper understanding of the micro-dynamics of collaborative team processes.
从运动和科学研究到日常生活，更高层次的追求都需要合作。尽管关于人类行为的基于数据的研究数量有所增加，但社交网络科学和其他计算及定量工具在很大程度上仍未探索协作问题解决的社会动态。在这里，我们将密室逃脱作为一种非干预性和最小偏见的社交实验室，它使我们能够以高分辨率实时捕获小项目团队中的沟通。我们的分析描绘了社会动态不同维度的细致画面。我们揭示了社会人口特征如何影响问题解决，以及先前关系对于增强互动的重要性。我们从模体分析中提取关键的对话规则，并讨论了特别强烈的男性主导团队中的夺话行为现象。我们研究了有符号和群体互动的时间演变，发现紧张沟通的最低水平可能有益于集体问题解决，并揭示了成功和失败团队行为的差异。我们的工作揭示了密室逃脱在研究团队复杂性方面的创新潜力，有助于更深入地了解协作团队过程的微观动态。
