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The Gestalt in Graphs: Prediction Using Economic Networks

机译:图中的格式塔:使用经济网络进行预测

摘要

We define an economic network as a linked set of entities, where links are created by actual realizations of shared economicoutcomes between entities. Such networks are becoming increasingly prevalent on the Internet, an example being the copurchase netwok on Amazon where entities are booksand links designate which pairs were purchased simultaneously. Our dataset covers a diverse set of books spanning over 400 categories over a period of three years with a total of over 70 million observations. To our knowledge, this is the first large scale study showing that an economic networkcontains useful predictive information that is distributed in the network. We show that an economic network contains predictive information. Specifically, we demonstrate that an entity’s future demand is more accurately predicted by combining its historical demand with that of its neighbors than by considering its demand alone. In other words, if you want to know what your state will be in the future, consider whatis happening to your neighbors now. This result could apply to other economic networks where outcomes of sets of entities tend to be related.
机译:我们将经济网络定义为一组链接的实体,其中链接是通过实体之间共享经济成果的实际实现而创建的。这样的网络在Internet上变得越来越普遍,例如在亚马逊上的共同购买网络,其中实体是书籍,链接指定同时购买了哪些对。我们的数据集涵盖了一系列的图书,这些图书在三年的时间内涵盖了400多个类别,总共观察到超过7,000万本图书。据我们所知,这是首次大规模研究,表明经济网络包含分布在网络中的有用预测信息。我们表明经济网络包含预测信息。具体来说,我们证明,将实体的历史需求与邻居的历史需求相结合,比仅考虑其需求会更准确地预测实体的未来需求。换句话说,如果您想知道将来的状态,请考虑一下邻居现在正在发生什么。该结果可能适用于其他经济网络,其中实体集的结果往往是相关的。

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