Migration Policies and Immigrants' Language Acquisition in EU-15
Evidence from Twitter
Bibliographic Data
| ID | 4120146 |
|---|---|
| Authors | Sofia Gil‐clavel (0000-0003-4707-849X), André Grow (0000-0003-2470-0071), Maarten J Bijlsma (0000-0002-7330-6006) |
| Year | 2023 |
| Volume | 49 |
| Issue | 3 |
| Pages | 469-497 |
| Publication date | 2023-09-01 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Population and Development Review (JOURNAL) |
| Journal identifiers | ISSN: 0098-7921 • E-ISSN: 1728-4457 |
| Publisher | Wiley (PUBLISHER • GB) |
| DOI | 10.1111/padr.12574 |
| OpenAlex | W4382403142 |
| Language | EN |
| Citations received | 5 |
| References cited | 69 |
In response to the increasingly complex and heterogeneous immigrant communities settling in Europe, European countries have adopted various civic integration measures. Measures aiming to facilitate language acquisition are considered crucial for integration and cooperation between immigrants and natives. Simultaneously, the rapid expansion of social media usage is believed to change the factors affecting immigrants' language acquisition. However, only a few previous studies have analyzed whether this is the case. This article uses a novel longitudinal data source derived from Twitter to (1) analyze differences in the pace of immigrants' language acquisition depending on the migration policies of destination countries and (2) study how the relative sizes of the migrant groups in destination countries, and the linguistic and geographical distances between origin and destination countries, are associated with language acquisition. Results show that immigrants who live in countries with strict language acquisition requirements for immigrants and conservative citizenship policies have the highest median times until language acquisition. Based on Twitter data, we also find that language acquisition is associated with classic explanatory variables, such as the size of the immigrant group in the destination country and the linguistic and geographical distance between origin and destination country similar to the previous studies
Citizenship · Demographic economics · Economics · Geography · Immigration · Language acquisition · Linguistics · Pace · Political science · Second-language acquisition · Social integration · Migration and Labor Dynamics · Migration, Refugees, and Integration · Social Media and Politics
The age of migration
Modeling Survival Data
Survival Analysis
Data Feminism
A topology of Twitter research
Social media and migration
Bilingual and second language interactions
Bilingualism in the Køge Project
Cultural Integration of Immigrants in Europe
German Multiculturalism
Native language, spoken language, translation and trade
Human Rights and Minority Languages
The path to naturalization in Spain
Geo-located Twitter as proxy for global mobility patterns
Validating integration and citizenship policy indices
Language testing, ‘integration’ and subtractive multilingualism in Italy
Potential Biases in Big Data
A Manifesto for Quantitative Multi-sited Approaches to International Migration
Analyzing the Effect of Time in Migration Measurement Using Georeferenced Digital Trace Data
A model of destination-language acquisition
Fortifying Citizenship
The Impact of the Far Right on Citizenship Policy in Europe
Language, employability and positioning in a Danish integration programme
Integration Requirements for Integration's Sake? Identifying, Categorising and Comparing Civic Integration Policies
English in contemporary Sweden
Siglo XVIII
Otherism in Discourses, Integration in Policies
Migrants in the Scandinavian Welfare State
Data ex Machina
Language Proficiency and Usage Among Immigrants in the Netherlands
Transformative Effects of Immigration Law
Destination-Language Proficiency in Cross-National Perspective
Why bother with testing? The validity of immigrants' self-assessed language proficiency
| Unique citing works | 5 |
|---|---|
| Citations per year | 2,5 |
| Citation span | 2024 - 2026 (3) |
| Citation velocity | current |
| Highly cited | No |
| Citation types | Neutral: 5 |