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Narratives of integration: Liminality in migrant acculturation through social media

Mitra, Amit; Evansluong, Quang

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Amit Mitra Amit.Mitra@uwe.ac.uk
Associate Professor in Strategy & Operations Management



Abstract

Migrant integration is a long drawn out process requiring synergies with various dimensions of life, rhyming with those of the host country. In this paper, we attempt to deconstruct the digital narratives of migrants to explore how they may lead to a meaningful assessment of their acculturation and consequent integration in their host societies'. Drawing on acculturation theory as a lens, we argue that migrants' use of social media creates a liminality that is synonymous to ambiguity and disorientation that may diminish through a composite adaptation of acculturation and ethnic identity. Our data evidence on social media use among migrants domiciled in major cities in Sweden suggest that social media-based interaction of migrants is not encouraging integration, while their digital proclivities tend to define their narratives of online ethnicity and their physical realities. Implications for migrant integration are presented.

Citation

Mitra, A., & Evansluong, Q. (2019). Narratives of integration: Liminality in migrant acculturation through social media. Technological Forecasting and Social Change, 145, 474-480. https://doi.org/10.1016/j.techfore.2019.01.011

Journal Article Type Article
Acceptance Date Jan 11, 2019
Online Publication Date Jan 24, 2019
Publication Date Aug 1, 2019
Deposit Date Jan 11, 2019
Publicly Available Date Mar 29, 2024
Journal Technological Forecasting and Social Change
Print ISSN 0040-1625
Publisher Elsevier
Peer Reviewed Peer Reviewed
Volume 145
Pages 474-480
DOI https://doi.org/10.1016/j.techfore.2019.01.011
Keywords acculturation, social media, migrant, ethnic identity, user generated content, community
Public URL https://uwe-repository.worktribe.com/output/853416
Publisher URL https://doi.org/10.1016/j.techfore.2019.01.011
Additional Information Additional Information : This is the author's accepted manuscript. The final published version is available at https://doi.org/10.1016/j.techfore.2019.01.011

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