流动人口的城市梦--以上海市流动人口融入为例
Urban Dreams of Migrants: A Case Study of Migrant Integration in Shanghai
摘要：
前所未有的人口流动推动了世界各地的快速城市化。在中国，居住在城市的人口比例从1978年的17.9%增加到2012年的52.6%。这种大规模的移徙给决策者带来了挑战，也给研究人员带来了重要问题。为了研究农民工融入社会的过程，我们使用了一个月的完整数据集的电信元数据在上海54万用户和6.98亿通话记录。我们发现当地人和移民在移动通信网络和地理位置方面存在系统性差异。例如，移民有更多样化的接触，在定居后，他们在城市周围的移动半径比当地人更大。通过区分新移民（最近搬到上海）和定居移民（已经在上海呆了一段时间），我们展示了新移民在前三周的融入过程。此外，我们制定分类问题来预测一个人是否是移民。我们的分类器在区分定居移民和当地人时能够达到0.82的F1分数，但由于阶级不平衡，识别新移民仍然具有挑战性。这种分类设置有希望识别将成功融入当地人的新移民（被误分类为当地人的新移民）。
英文摘要：
Unprecedented human mobility has driven the rapid urbanization around the world. In China, the fraction of population dwelling in cities increased from 17.9% to 52.6% between 1978 and 2012. Such large-scale migration poses challenges for policymakers and important questions for researchers. To investigate the process of migrant integration, we employ a one-month complete dataset of telecommunication metadata in Shanghai with 54 million users and 698 million call logs. We find systematic differences between locals and migrants in their mobile communication networks and geographical locations. For instance, migrants have more diverse contacts and move around the city with a larger radius than locals after they settle down. By distinguishing new migrants (who recently moved to Shanghai) from settled migrants (who have been in Shanghai for a while), we demonstrate the integration process of new migrants in their first three weeks. Moreover, we formulate classification problems to predict whether a person is a migrant. Our classifier is able to achieve an F1-score of 0.82 when distinguishing settled migrants from locals, but it remains challenging to identify new migrants because of class imbalance. This classification setup holds promise for identifying new migrants who will successfully integrate into locals (new migrants that misclassified as locals).
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。
