Estimating the Irregular Migrant Population Through Social Media Surveys

International migrants are a hard-to-reach population, which is often challenging to survey due to difficulties in capturing certain groups within standard sampling frames, such as population registers or censuses. Surveying irregular migrants is particularly complex given their heightened concerns about detection. In recent years, innovative approaches using social media platforms have shown promise in recruiting under-represented groups for online surveys. However, existing research has not systematically distinguished migrants by legal status, leaving unanswered questions about whether social media recruitment is a feasible and effective method for surveying irregular migrants.This Briefing Paper outlines the design and implementation of an online survey targeting Mexican and Venezuelan migrants in four U.S. states, recruited through targeted Facebook advertisements. We discuss findings related to implementation, sampling, coverage, and the elicitation of legal status, comparing methods such as direct questions and list experiments. Our results demonstrate that Facebook surveys are a feasible, low-cost, and rapid approach to recruiting sizable samples of international migrants, including irregular migrants. Furthermore, we find that list experiments yield less biased estimates of irregular status compared to direct questioning, particularly for Mexicans migrants. While our survey-based estimates of the proportion of irregular migrants align closely with existing estimates, we highlight challenges related to survey implementation and potential sample biases.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-04-07
DOI
https://doi.org/10.5281/zenodo.14801998
Primary Topic
Survey Methodology and Nonresponse
Type
article
Field-Weighted Citation Impact
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article

Estimating the Irregular Migrant Population Through Social Media Surveys

Zenodo (CERN European Organization for Nuclear Research)
Survey Methodology and Nonresponse
article

Estimating the Irregular Migrant Population Through Social Media Surveys

article en

Abstract

International migrants are a hard-to-reach population, which is often challenging to survey due to difficulties in capturing certain groups within standard sampling frames, such as population registers or censuses. Surveying irregular migrants is particularly complex given their heightened concerns about detection. In recent years, innovative approaches using social media platforms have shown promise in recruiting under-represented groups for online surveys. However, existing research has not systematically distinguished migrants by legal status, leaving unanswered questions about whether social media recruitment is a feasible and effective method for surveying irregular migrants.This Briefing Paper outlines the design and implementation of an online survey targeting Mexican and Venezuelan migrants in four U.S. states, recruited through targeted Facebook advertisements. We discuss findings related to implementation, sampling, coverage, and the elicitation of legal status, comparing methods such as direct questions and list experiments. Our results demonstrate that Facebook surveys are a feasible, low-cost, and rapid approach to recruiting sizable samples of international migrants, including irregular migrants. Furthermore, we find that list experiments yield less biased estimates of irregular status compared to direct questioning, particularly for Mexicans migrants. While our survey-based estimates of the proportion of irregular migrants align closely with existing estimates, we highlight challenges related to survey implementation and potential sample biases.

Zenodo (CERN European Organization for Nuclear Research)
University of Potsdam (DE)
Reduced inequalities
Openalex Percentile: Top 49%
Survey Methodology and Nonresponse
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Estimating the Irregular Migrant Population Through Social Media Surveys · Zenodo (CERN European Organization for Nuclear Research) (2025) | TGRS Research Map | TGRS