Analyzing EU-15 immigrants’ language acquisition using Twitter data
B. Sofia Gil-Clavel,
André Grow and
Maarten J. Bijlsma
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B. Sofia Gil-Clavel: Max Planck Institute for Demographic Research, Rostock, Germany
André Grow: Max Planck Institute for Demographic Research, Rostock, Germany
Maarten J. Bijlsma: Max Planck Institute for Demographic Research, Rostock, Germany
No WP-2022-012, MPIDR Working Papers from Max Planck Institute for Demographic Research, Rostock, Germany
The increasingly complex and heterogeneous immigrant communities settling in Europe have led European countries to adopt civic-integration measures. Among these, measures that aim to facilitate language acquisition are often considered crucial for integration and cooperation between immigrants and natives. Simultaneously, the rapid expansion of the use of online social networks is believed to change the factors that affect immigrants’ language acquisition. However, so far, few studies have analyzed whether this is the case. This article uses a novel longitudinal data source derived from Twitter to: (1) analyze differences between destination-countries in the pace of immigrants’ language acquisition depending on the citizenship and civic-integration policies of those countries; and (2) study how the relative size of migrant groups in the destination-country, and the linguistic and geographical distance between origin- and destination countries, are associated with language acquisition. We focus on immigrants whose destination countries were in the EU-15 between 2012 and 2016. We study time until a user mostly tweets in the language of the destination-country for one month as a proxy of language acquisition using survival analysis. Results show that immigrants who live in countries with strict requirements for immigrants’ language acquisition and low levels of liberal citizenship policies have the highest median times of language acquisition. Furthermore, on social media such as Twitter, language acquisition is associated with classic explanatory variables, such as size of the immigrant group in the destination country, linguistic distance between origin- and destination-language, and geographical distance between origin- and destination-country.
Keywords: European Union; computational social science; culture; immigration policy; international migration; languages (search for similar items in EconPapers)
JEL-codes: J1 Z0 (search for similar items in EconPapers)
Pages: 32 pages
New Economics Papers: this item is included in nep-ban, nep-cmp, nep-eur, nep-int, nep-mig and nep-ure
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Persistent link: https://EconPapers.repec.org/RePEc:dem:wpaper:wp-2022-012
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