使用通信模式推断人类流动
Inferring human mobility using communication patterns
摘要：
出于多种原因，从城市规划到灾害管理，了解个人的流动模式至关重要。有两种常用的方法来量化地点之间的旅行量：通过直接观察，通常涉及隐私问题，例如，跟踪移动电话位置，或者通过模型的估计。通常，这种模型建立在对每个地点的人口规模的准确了解的基础上。然而，如果这一信息不容易获得，其适用性就相当有限。由于移动电话是无处不在的，我们的目的是调查，如果移动模式可以推断从聚合的移动电话通话数据。使用Orange为象牙海岸发布的数据，我们表明，人类流动是很好地预测一个简单的模型的基础上，两个地点之间的移动电话的频率和他们的地理距离。我们认为，该模型的力量来自直接纳入流动性的社会层面。此外，由于只需要聚合的呼叫数据，该模型有助于避免潜在的隐私问题。
英文摘要：
Understanding the patterns of mobility of individuals is crucial for a number of reasons, from city planning to disaster management. There are two common ways of quantifying the amount of travel between locations: by direct observations that often involve privacy issues, e.g., tracking mobile phone locations, or by estimations from models. Typically, such models build on accurate knowledge of the population size at each location. However, when this information is not readily available, their applicability is rather limited. As mobile phones are ubiquitous, our aim is to investigate if mobility patterns can be inferred from aggregated mobile phone call data alone. Using data released by Orange for Ivory Coast, we show that human mobility is well predicted by a simple model based on the frequency of mobile phone calls between two locations and their geographical distance. We argue that the strength of the model comes from directly incorporating the social dimension of mobility. Furthermore, as only aggregated call data is required, the model helps to avoid potential privacy problems.
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