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 more accurately reflect human understanding and evaluation of migration events, and further provide more granular insight into migration spells and types than what are captured in standard survey instruments.
Highlights
Migrants play an important role in all aspects of modern society
The individual’s most frequent location for the first three months was different from the most frequent location for the last three months, but in reality the individual lived in the border region between the two locations, and did not migrate. To fill these gaps in the literature and enable future empirical work on migration, this paper develops a novel and general approach to detecting migration events in large-scale digital trace data
The methods we describe in this paper are meant to provide more accurate and robust measurements of human migration, and while our goal is to enable social science research and pro-social applications, we acknowledge the potential for anti-social uses
Summary
Migrants play an important role in all aspects of modern society. It is estimated that about 0.6% of the world population migrated internationally from 2005 to 2010 [1]. A general approach to detecting migration events in digital trace data More recently, the research literature has defined a migration event as “a change in the place of usual residence, which involves crossing a recognized political/administrative border” [29]. This usually involves specifying a temporal dimension and a spatial dimension [30, 31]. The World Bank’s Livings Standards and Measurements Survey, conducted primarily in developing countries, contains a migration module that queries place of birth, the year that households moved into the current housing unit, and other relevant information [29, 33]
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