论文标题
通过时间上下文来表征人类在数字平台中的行动
Characterizing Human Actions in the Digital Platform by Temporal Context
论文作者
论文摘要
数字平台的最新进展产生了人类行为的丰富，高维的日志，机器学习模型帮助社会科学家解释了知识的积累，沟通和信息扩散。然而，这种模型几乎总是将行为视为动作序列，从而在动作之间抽象了时空信息。为了缩小这一差距，我们引入了一个两尺度的动作观点（ATC）框架，该框架共同嵌入了每个动作及其时间间隔。 ATC获得了动作的低维表示，并通过时空信息进行表征。我们提供了ATC到现实世界数据集的三种应用，并证明该方法提供了人类行为的统一观点。提出的定性发现表明，明确建模到跨时空的环境对于对数字平台上人类活动的全面理解至关重要。
Recent advances in digital platforms generate rich, high-dimensional logs of human behavior, and machine learning models have helped social scientists explain knowledge accumulation, communication, and information diffusion. Such models, however, almost always treat behavior as sequences of actions, abstracting the inter-temporal information among actions. To close this gap, we introduce a two-scale Action-Timing Context(ATC) framework that jointly embeds each action and its time interval. ATC obtains low-dimensional representations of actions and characterizes them with inter-temporal information. We provide three applications of ATC to real-world datasets and demonstrate that the method offers a unified view of human behavior. The presented qualitative findings demonstrate that explicitly modeling inter-temporal context is essential for a comprehensive, interpretable understanding of human activity on digital platforms.
