Studying migrant assimilation through Facebook interests

Antoine Dubois; Emilio Zagheni; Kiran Garimella; Ingmar Weber

doi:10.1007/978-3-030-01159-8_5

Studying migrant assimilation through Facebook interests

Antoine Dubois, Emilio Zagheni, Kiran Garimella^*, Ingmar Weber

^*Corresponding author for this work

Department of Computer Science

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review

10 Citations (Scopus)

Abstract

Migrant assimilation is a major challenge for European societies, in part because of the sudden surge of refugees in recent years and in part because of long-term demographic trends. In this paper, we use Facebook data for advertisers to study the levels of assimilation of Arabic-speaking migrants in Germany, as seen through the interests they express online. Our results indicate a gradient of assimilation along demographic lines, language spoken and country of origin. Given the difficulty to collect timely migration data, in particular for traits related to cultural assimilation, the methods that we develop and the results that we provide open new lines of research that computational social scientists are well-positioned to address.

Original language	English
Title of host publication	Social Informatics - 10th International Conference, SocInfo 2018, Proceedings
Editors	Steffen Staab, Olessia Koltsova, Dmitry I. Ignatov
Pages	51-60
Number of pages	10
DOIs	https://doi.org/10.1007/978-3-030-01159-8_5
Publication status	Published - 1 Jan 2018
MoE publication type	A4 Article in a conference publication
Event	Conference on Social Informatics - Saint-Petersburg, Russian Federation Duration: 25 Sep 2018 → 28 Sep 2018 Conference number: 10

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	11186 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	Conference on Social Informatics
Abbreviated title	SocInfo
Country	Russian Federation
City	Saint-Petersburg
Period	25/09/2018 → 28/09/2018

Access to Document

10.1007/978-3-030-01159-8_5

Link to publication in Scopus

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Dubois, A., Zagheni, E., Garimella, K., & Weber, I. (2018). Studying migrant assimilation through Facebook interests. In S. Staab, O. Koltsova, & D. I. Ignatov (Eds.), Social Informatics - 10th International Conference, SocInfo 2018, Proceedings (pp. 51-60). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11186 LNCS). https://doi.org/10.1007/978-3-030-01159-8_5

Dubois, Antoine ; Zagheni, Emilio ; Garimella, Kiran ; Weber, Ingmar. / Studying migrant assimilation through Facebook interests. Social Informatics - 10th International Conference, SocInfo 2018, Proceedings. editor / Steffen Staab ; Olessia Koltsova ; Dmitry I. Ignatov. 2018. pp. 51-60 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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abstract = "Migrant assimilation is a major challenge for European societies, in part because of the sudden surge of refugees in recent years and in part because of long-term demographic trends. In this paper, we use Facebook data for advertisers to study the levels of assimilation of Arabic-speaking migrants in Germany, as seen through the interests they express online. Our results indicate a gradient of assimilation along demographic lines, language spoken and country of origin. Given the difficulty to collect timely migration data, in particular for traits related to cultural assimilation, the methods that we develop and the results that we provide open new lines of research that computational social scientists are well-positioned to address.",

author = "Antoine Dubois and Emilio Zagheni and Kiran Garimella and Ingmar Weber",

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Dubois, A, Zagheni, E, Garimella, K & Weber, I 2018, Studying migrant assimilation through Facebook interests. in S Staab, O Koltsova & DI Ignatov (eds), Social Informatics - 10th International Conference, SocInfo 2018, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 11186 LNCS, pp. 51-60, Conference on Social Informatics, Saint-Petersburg, Russian Federation, 25/09/2018. https://doi.org/10.1007/978-3-030-01159-8_5

Studying migrant assimilation through Facebook interests. / Dubois, Antoine; Zagheni, Emilio; Garimella, Kiran; Weber, Ingmar.

Social Informatics - 10th International Conference, SocInfo 2018, Proceedings. ed. / Steffen Staab; Olessia Koltsova; Dmitry I. Ignatov. 2018. p. 51-60 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11186 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review

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AB - Migrant assimilation is a major challenge for European societies, in part because of the sudden surge of refugees in recent years and in part because of long-term demographic trends. In this paper, we use Facebook data for advertisers to study the levels of assimilation of Arabic-speaking migrants in Germany, as seen through the interests they express online. Our results indicate a gradient of assimilation along demographic lines, language spoken and country of origin. Given the difficulty to collect timely migration data, in particular for traits related to cultural assimilation, the methods that we develop and the results that we provide open new lines of research that computational social scientists are well-positioned to address.

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Dubois A, Zagheni E, Garimella K, Weber I. Studying migrant assimilation through Facebook interests. In Staab S, Koltsova O, Ignatov DI, editors, Social Informatics - 10th International Conference, SocInfo 2018, Proceedings. 2018. p. 51-60. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-030-01159-8_5