Advances in information technology have increased the availability of time-stamped relational data such as those produced by email exchanges or interaction through social media. Whereas the associated information flows could be aggregated into cross-sectional panels, the temporal ordering of the events frequently contains information that requires new models for the analysis of continuous-time interactions, subject to both endogenous and exogenous influences. The introduction of the Relational Event Model (REM) has been a major development that has led to further methodological improvements stimulated by new questions that REMs made possible. In this review, we track the intellectual history of the REM, define its core properties, and discuss why and how it has been considered useful in empirical research. We describe how the demands of novel applications have stimulated methodological, computational, and inferential advancements.

翻译：信息技术的进步增加了时间戳关系数据的可用性，例如电子邮件往来或社交媒体互动所产生的数据。尽管相关信息流可被整合为截面面板数据，但事件的时间顺序通常包含信息，需要新的模型来分析受内生和外生影响共同作用的连续时间交互。关系事件模型（REM）的引入是一项重大发展，它通过REM引发的新问题推动了进一步的方法论改进。本综述梳理了REM的学术发展历程，界定了其核心属性，并探讨了其在实证研究中被认为有用的原因及方式。我们阐述了新型应用需求如何刺激了方法论、计算及推断层面的进步。