Tracking Human Migration from Online Attention

被引：1

作者：

Vaca-Ruiz, Carmen ^{[1
,2
]}

Quercia, Daniele ^{[2
]}

Maria Aiello, Luca ^{[2
]}

Fraternali, Piero ^{[1
]}

机构：

[1] Politecn Milan, I-20133 Milan, Italy

[2] Yahoo Res, Barcelona, Spain

来源：

CITIZEN IN SENSOR NETWORKS | 2014年 / 8313卷

关键词：

D O I：

10.1007/978-3-319-04178-0_7

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

The dynamics behind human migrations are very complex. Economists have intensely studied them because of their importance for the global economy. However, tracking migration is costly, and available data tends to be outdated. Online data can be used to extract proxies for migration flows, and these proxies would not be meant to replicate traditional measurements but are meant to complement them. We analyze a random sample of a microblogging service popular in Brazil (more than 13M posts and 22M reposts) and accurately predict the total number of migrants in 35 Brazilian cities. These results are so accurate that they have promising implications in monitoring emerging economies.

引用

页码：73 / 83

页数：11

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PLOS ONE, 2013, 8 (01)

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