从官方统计的移动电话数据评估家庭检测质量
Assessing the quality of home detection from mobile phone data for official statistics
摘要：
移动电话数据是官方统计的一个有趣的新数据来源。然而，在这些数据能够提供信息、支持甚至成为统计编制过程的一个组成部分之前，需要解决多种问题和不确定性。在本文中，我们专注于可以说是最重要的问题，阻碍了移动电话数据在官方统计中的应用：检测家庭位置。我们认为，目前的努力，以检测家庭的位置遭受盲目部署的标准来定义一个居住地和有限的验证可能性。我们通过分析五种家庭检测算法（HDA）的性能来支持我们的论点，这些算法已应用于一个大型的法国电话详细记录（CDR）数据集（约1800万用户，5个月）。我们的研究结果表明，HDAs的标准选择影响了高达约40%的用户的家庭位置的检测，HDAs表现不佳时，与验证数据集（35°的差距）相比，他们的表现是敏感的时间段和观察的持续时间。根据我们的调查结果和经验，我们对官方统计提出了几项建议。我们的建议如获采纳，将有助于确保相对于官方统计数据而言，更可靠地使用移动电话数据。
英文摘要：
Mobile phone data are an interesting new data source for official statistics. However, multiple problems and uncertainties need to be solved before these data can inform, support or even become an integral part of statistical production processes. In this paper, we focus on arguably the most important problem hindering the application of mobile phone data in official statistics: detecting home locations. We argue that current efforts to detect home locations suffer from a blind deployment of criteria to define a place of residence and from limited validation possibilities. We support our argument by analysing the performance of five home detection algorithms (HDAs) that have been applied to a large, French, Call Detailed Record (CDR) dataset (~18 million users, 5 months). Our results show that criteria choice in HDAs influences the detection of home locations for up to about 40% of users, that HDAs perform poorly when compared with a validation dataset (the 35°-gap), and that their performance is sensitive to the time period and the duration of observation. Based on our findings and experiences, we offer several recommendations for official statistics. If adopted, our recommendations would help in ensuring a more reliable use of mobile phone data vis-à-vis official statistics.
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。
