Migration data using social media: a European perspective

Spyridon Spyratos · Michele Vespe · Fabrizio Natale · Ingmar G. Weber · Emilio Zagheni · Marzia Rango

95 citations0/0 files storedJoint Research Centre (European Commission)

No readable copy stored yet — this record is metadata only.

No open-access location is known for this record yet.

Literature note Cite in a project Citation map

Human Mobility and Location-Based Analysis Migration and Labor Dynamics Census and Population Estimation

Abstract

Migration is a top political priority for the European Union (EU). Data on international migrant stocks and flows are essential for effective migration management. In this report, we estimated the number of expatriates in 17 EU countries based on the number of Facebook Network users who are classified by Facebook as “expats”. To this end, we proposed a method for correcting the over- or under-representativeness of Facebook Network users compared to countries’ actual population. This method uses Facebook penetration rates by age group and gender in the country of previous residence and country of destination of a Facebook expat. The purpose of Facebook Network expat estimations is not to reproduce migration statistics, but rather to generate separate estimates of expatriates, since migration statistics and Facebook Network expats estimates do not measure the same quantities of interest. Estimates of social media application users who are classified as expats can be a timely, low-cost, and almost globally available source of information for estimating stocks of international migrants. Our methodology allowed for the timely capture of the increase of Venezuelan migrants in Spain. However, there are important methodological and data integrity issues with using social media data sources for studying migration-related phenomena. For example, our methodology led us to significantly overestimate the number of expats from Philippines in Spain and in Italy and there is no evidence that this overestimation may be valid. While research on the use of big data sources for migration is in its infancy, and the diffusion of internet technologies in less developed countries is still limited, the use of big data sources can unveil useful insights on quantitative and qualitative characteristics of migration.

Paper brief

Loading…

Cite this work

Citation unavailable for this work.

BibTeX RIS CSL-JSON

No public copy is stored for this record, so only the metadata is cited.

Citations in this library

Citation map →

Stored only when both papers are in the corpus — 95 citations exist upstream.

References

2014Geo-located Twitter as proxy for global mobility patterns 2014Inferring international and internal migration patterns from Twitter data

Cited by

2020International migration management in the age of artificial intelligence 2020Using geotagged tweets to track population movements to and from Puerto Rico after Hurricane Maria 2019Quantifying international human mobility patterns using Facebook Network data 2019Dissecting global air traffic data to discern different types and trends of transnational human mobility 2020How well can we estimate immigration trends using Google data?2021Influencers, Backfire Effects, and the Power of the Periphery 2024Integrating Traditional and Social Media Data to Predict Bilateral Migrant Stocks in the European Union 2021Introducing Twitter Daily Estimates of Residents and Non-Residents at the County Level

Explore the map →

Papers that cite the same references — the relational fallback while embeddings are still backfilling.

Imported from OpenAlex (CC0) — nothing here is generated.