In this article, we explore the relationship between cellular phone data and housing prices in Budapest, Hungary. We determine mobility indicators from one months of Call Detail Records (CDR) data, while the property price data are used to characterize the socioeconomic status at the Capital of Hungary. First, we validated the proposed methodology by comparing the Home and Work locations estimation and the commuting patterns derived from the cellular network dataset with reports of the national mini census. We investigated the statistical relationships between mobile phone indicators, such as Radius of Gyration, the distance between Home and Work locations or the Entropy of visited cells, and measures of economic status based on housing prices. Our findings show that the mobility correlates significantly with the socioeconomic status. We performed Principal Component Analysis (PCA) on combined vectors of mobility indicators in order to characterize the dependence of mobility habits on socioeconomic status. The results of the PCA investigation showed remarkable correlation of housing prices and mobility customs.

中文翻译：

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评估财务状况对流动海关的影响

在本文中，我们探讨了匈牙利布达佩斯的手机数据与房价之间的关系。我们根据一个月的通话详细记录 (CDR) 数据确定流动性指标，而房地产价格数据则用于表征匈牙利首都的社会经济状况。首先，我们通过比较来自蜂窝网络数据集的家庭和工作位置估计以及通勤模式与国家小型人口普查报告来验证所提出的方法。我们调查了手机指标之间的统计关系，例如回转半径、家庭和工作地点之间的距离或访问单元的熵，以及基于房价的经济状况度量。我们的研究结果表明，流动性与社会经济地位显着相关。我们对流动性指标的组合向量进行了主成分分析 (PCA)，以表征流动性习惯对社会经济地位的依赖性。PCA 调查的结果显示，房价与出行习惯之间存在显着的相关性。