双边互联网平台上的用户流量。定性动力学
Users' traffic on two-sided Internet platforms. Qualitative dynamics
摘要：
互联网平台的流量定义了平台的重要特征，例如服务定价、广告、运营速度。人们可以用传统的时间序列模型，如ARIMA，Holt-Winters，函数和核回归来估计流量。当使用这些方法时，我们通常会平滑数据中的噪声和各种外部影响，并获得过程的短期预测。然而，这些模型并不一定能帮助我们理解这些过程的潜在机制和趋势。在这篇文章中，我们讨论了动力系统的建模方法，旨在发现潜在的机制和系统的相图的定性属性。我们将展示如何从数据中重建控制微分方程。外部效应被建模为系统的参数（初始条件）。利用这种新的方法，我们构建了模型的用户量，通过互联网平台，如“Amazon.com”，“Homes.mil”或“Wikipedia.org”进行交互。然后，我们进行定性分析的系统的阶段画像，并讨论了平台的主要特点。
英文摘要：
Internet platforms' traffic defines important characteristics of platforms, such as pricing of services, advertisements, speed of operations. One can estimate the traffic with the traditional time series models like ARIMA, Holt-Winters, functional and kernel regressions. When using these methods, we usually smooth-out noise and various external effects in the data and obtain short-term predictions of processes. However, these models do not necessarily help us to understand the underlying mechanism and the tendencies of the processes. In this article, we discuss the dynamical system approach to the modeling, which is designed to discover the underlying mechanism and the qualitative properties of the system's phase portrait. We show how to reconstruct the governing differential equations from data. The external effects are modeled as system's parameters (initial conditions). Utilizing this new approach, we construct the models for the volume of users, interacting through Internet platforms, such as "Amazon.com", "Homes.mil" or "Wikipedia.org". Then, we perform qualitative analysis of the system's phase portrait and discuss the main characteristics of the platforms.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
