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A General Approach to Detecting Migration Events in Digital Trace Data

Version
V0
Resource Type
Dataset
Creator
  • Chi, Guanghua (University of California-Berkeley)
Publication Date
2020-07-12
Description
  • Abstract

    Empirical research on migration has historically been fraught with measurement challenges. Recently, the increasing ubiquity of digital trace data — from mobile phones, social media, and related sources of ‘big data’ — has created new opportunities for the quantitative analysis of migration. However, most existing work relies on relatively ad hoc methods for inferring migration. Here, we develop and validate a novel and general approach to detecting migration events in trace data. We benchmark this method using two different trace datasets: four years of mobile phone metadata from a single country’s monopoly operator, and three years of geo-tagged Twitter data. The novel measures accurately reflect existing knowledge of migration in these contexts, and also provide more granular insight into migration spells and types than what are captured in standard survey instruments.
Availability
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Update Metadata: 2020-07-12 | Issue Number: 2 | Registration Date: 2020-01-17

Chi, Guanghua (2020): A General Approach to Detecting Migration Events in Digital Trace Data. Version: V0. ICPSR - Interuniversity Consortium for Political and Social Research. Dataset. https://doi.org/10.3886/E117242