Chatty手机：个人移动性和通信模式
Chatty Mobiles:Individual mobility and communication patterns
摘要：
人口流动性分析是社会科学中的一个重要问题，而流动性数据是乌尔数据库研究、地理、交通和领土管理中最受欢迎的信息来源之一。在网络科学中，移动性研究在过去几年中变得流行，特别是使用移动电话位置数据。为了保护客户隐私，电信运营商提供的数据集是匿名的。与此同时，数据集的大规模往往使得计算所有观测到的轨迹的任务非常困难和耗时。一个解决方案可能是抽样用户。然而，没有关于移动用户的信息的事实使得采样变得微妙。一些研究人员从他们的数据集中随机选择用户样本。其他人试图优化这种方法，例如，只考虑具有一定数量或频率的位置记录的用户。乍一看，第二种选择似乎更有效：拥有更多的个体轨迹使分析更精确。然而，最常用的CDR数据（呼叫详细记录）仅在通信（呼叫、SMS、数据连接）时生成位置。由于这一事实，用户的移动模式不能精确地建立在他们的通信模式。因此，这些数据在空间和时间尺度上都具有明显的短期性。在本文中，我们提出了估计之间的相关性的用户通信和移动性，以便更好地评估基于频率的采样的偏差。使用技术GSM网络数据（包括通信，但也独立的移动记录），我们将分析通信和移动模式之间的关系。
英文摘要：
Human mobility analysis is an important issue in social sciences, and mobility data are among the most sought-after sources of information in ur- Data ban studies, geography, transportation and territory management. In network sciences mobility studies have become popular in the past few years, especially using mobile phone location data. For preserving the customer privacy, datasets furnished by telecom operators are anonymized. At the same time, the large size of datasets often makes the task of calculating all observed trajectories very difficult and time-consuming. One solution could be to sample users. However, the fact of not having information about the mobile user makes the sampling delicate. Some researchers select randomly a sample of users from their dataset. Others try to optimize this method, for example, taking into account only users with a certain number or frequency of locations recorded. At the first glance, the second choice seems to be more efficient: having more individual traces makes the analysis more precise. However, the most frequently used CDR data (Call Detail Records) have location generated only at the moment of communication (call, SMS, data connection). Due to this fact, users mobility patterns cannot be precisely built upon their communication patterns. Hence, these data have evident short-comings both in terms of spatial and temporal scale. In this paper we propose to estimate the correlation between the users communication and mo- bility in order to better assess the bias of frequency based sampling. Using technical GSM network data (including communication but also independent mobility records), we will analyze the relationship between communication and mobility patterns.
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。
