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An Adaptive Social Network Model for Expatriate Integration Based on Bonding by Homophily and Interaction Connects

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Computational Collective Intelligence (ICCCI 2022)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 13501))

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Abstract

This paper introduces a new view on modelling expatriate integration by mapping connections between expats and between expats and the local community. The proposed adaptive social network model differs from existing integration models in that it considers both the bonding by homophily principle together with the interaction connects principle to model the adaptivity of the strength of social connections. In the results it was found that both principles have different influences on how well expats integrate with the local community; a combination of both principles showed to be stronger than their sum.

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Authors and Affiliations

  1. Computational Science, University of Amsterdam, Amsterdam, The Netherlands

    Kamiel Gülpen & Dante de Lang

  2. Social AI Group, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands

    Jan Treur

Authors
  1. Kamiel Gülpen
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  2. Dante de Lang
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  3. Jan Treur
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Corresponding author

Correspondence to Jan Treur .

Editor information

Editors and Affiliations

  1. Wrocław University of Science and Technology, Wrocław, Poland

    Ngoc Thanh Nguyen

  2. Open University of Cyprus, Nicosia, Cyprus

    Yannis Manolopoulos

  3. University of Pau and Pays de l'Adour, Anglet, France

    Richard Chbeir

  4. Wrocław University of Science and Technology, Wrocław, Poland

    Adrianna Kozierkiewicz

  5. Wrocław University of Science and Technology, Wrocław, Poland

    Bogdan Trawiński

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Gülpen, K., de Lang, D., Treur, J. (2022). An Adaptive Social Network Model for Expatriate Integration Based on Bonding by Homophily and Interaction Connects. In: Nguyen, N.T., Manolopoulos, Y., Chbeir, R., Kozierkiewicz, A., Trawiński, B. (eds) Computational Collective Intelligence. ICCCI 2022. Lecture Notes in Computer Science(), vol 13501. Springer, Cham. https://doi.org/10.1007/978-3-031-16014-1_41

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  • DOI: https://doi.org/10.1007/978-3-031-16014-1_41

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  • Print ISBN: 978-3-031-16013-4

  • Online ISBN: 978-3-031-16014-1

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