Analyzing the effect of time in migration measurement using georeferenced digital trace data

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• dc.contributor.author Fiorio, Lee
• dc.contributor.author Zagheni, Emilio
• dc.contributor.author Abel, Guy
• dc.contributor.author Hill, Johnathan
• dc.contributor.author Pestre, Gabriel
• dc.contributor.author Letouzé, Emmanuel
• dc.contributor.author Cai, Jixuan
• dc.date.accessioned 2022-11-15T07:06:08Z
• dc.date.available 2022-11-15T07:06:08Z
• dc.date.issued 2021
• dc.description.abstract Georeferenced digital trace data offer unprecedented flexibility in migration estimation. Because of their high temporal granularity, many migration estimates can be generated from the same data set by changing the definition parameters. Yet despite the growing application of digital trace data to migration research, strategies for taking advantage of their temporal granularity remain largely underdeveloped. In this paper, we provide a general framework for converting digital trace data into estimates of migration transitions and for systematically analyzing their variation along a quasi-continuous time scale, analogous to a survival function. From migration theory, we develop two simple hypotheses regarding how we expect our estimated migration transition functions to behave. We then test our hypotheses on simulated data and empirical data from three platforms in two internal migration contexts: geotagged Tweets and Gowalla check-ins in the United States, and cell-phone call detail records in Senegal. Our results demonstrate the need for evaluating the internal consistency of migration estimates derived from digital trace data before using them in substantive research. At the same time, however, common patterns across our three empirical data sets point to an emergent research agenda using digital trace data to study the specific functional relationship between estimates of migration and time and how this relationship varies by geography and population characteristics.
• dc.format.mimetype application/pdf
• dc.identifier.citation Fiorio L, Zagheni E, Abel G, Hill J, Pestre G, Letouzé E, et al. Analyzing the effect of time in migration measurement using georeferenced digital trace data. Demography. 2021 Feb 1;58(1):51-74. DOI: 10.1215/00703370-8917630
• dc.identifier.doi http://dx.doi.org/10.1215/00703370-8917630
• dc.identifier.issn 0070-3370
• dc.identifier.uri http://hdl.handle.net/10230/54837
• dc.language.iso eng
• dc.publisher Duke University Press
• dc.relation.ispartof Demography. 2021 Feb 1;58(1):51-74
• dc.rights This is an open access article distributed under the terms of a Creative Commons license (CC BY-NC-ND 4.0).
• dc.rights.accessRights info:eu-repo/semantics/openAccess
• dc.rights.uri http://creativecommons.org/licenses/by-nc-nd/4.0/
• dc.subject.keyword Migration
• dc.subject.keyword Mobility
• dc.subject.keyword Big data
• dc.subject.keyword Methods
• dc.title Analyzing the effect of time in migration measurement using georeferenced digital trace data
• dc.type info:eu-repo/semantics/article
• dc.type.version info:eu-repo/semantics/publishedVersion