Department of Methodology & Statistics, Tilburg University, Warandelaan 2, 5037, AB, Tilburg, The Netherlands.
Department of Psychology, University of Münster, Münster, Germany.
Behav Res Methods. 2023 Apr;55(3):997-1023. doi: 10.3758/s13428-022-01821-8. Epub 2022 May 10.
Real-life social interactions occur in continuous time and are driven by complex mechanisms. Each interaction is not only affected by the characteristics of individuals or the environmental context but also by the history of interactions. The relational event framework provides a flexible approach to studying the mechanisms that drive how a sequence of social interactions evolves over time. This paper presents an introduction of this new statistical framework and two of its extensions for psychological researchers. The relational event framework is illustrated with an exemplary study on social interactions between freshmen students at the start of their new studies. We show how the framework can be used to study: (a) which predictors are important drivers of social interactions between freshmen students who start interacting at zero acquaintance; (b) how the effects of predictors change over time as acquaintance increases; and (c) the dynamics between the different settings in which students interact. Findings show that patterns of interaction developed early in the freshmen student network and remained relatively stable over time. Furthermore, clusters of interacting students formed quickly, and predominantly within a specific setting for interaction. Extraversion predicted rates of social interaction, and this effect was particularly pronounced on the weekends. These results illustrate how the relational event framework and its extensions can lead to new insights on social interactions and how they are affected both by the interacting individuals and the dynamic social environment.
现实生活中的社交互动是在连续的时间内发生的，并受到复杂机制的驱动。每一次互动不仅受到个体特征或环境背景的影响，还受到互动历史的影响。关系事件框架为研究驱动社会互动随时间演变的机制提供了一种灵活的方法。本文介绍了这个新的统计框架及其两个扩展，供心理学研究人员使用。关系事件框架通过一项关于新生在开始新学业时互动的示例研究进行了说明。我们展示了如何使用该框架研究：（a）在零相识度开始互动的新生之间，哪些预测因素是社交互动的重要驱动因素；（b）随着相识度的增加，预测因素的影响如何随时间变化；以及（c）学生互动的不同环境之间的动态关系。研究结果表明，新生网络中早期形成的互动模式随着时间的推移相对稳定。此外，互动的学生群体迅速形成，主要是在特定的互动环境中。外向性预测了社交互动的频率，而这种影响在周末尤为明显。这些结果说明了关系事件框架及其扩展如何能够深入了解社交互动以及互动个体和动态社交环境如何影响社交互动。
