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An analysis of Koreans' attitudes towards migrants by application of algorithmic approaches
Exclusivist behaviours toward migrants manifest not only from poor receptivity to multiculturalism, but also from competition for resources and opportunities such as job opportunities. This study analyses the socio-economic background of Koreans by categorizing them in terms of their receptivity to...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2022
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9420350/ https://www.ncbi.nlm.nih.gov/pubmed/36042735 http://dx.doi.org/10.1016/j.heliyon.2022.e10087 |
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author | Han, Seungwoo |
author_facet | Han, Seungwoo |
author_sort | Han, Seungwoo |
collection | PubMed |
description | Exclusivist behaviours toward migrants manifest not only from poor receptivity to multiculturalism, but also from competition for resources and opportunities such as job opportunities. This study analyses the socio-economic background of Koreans by categorizing them in terms of their receptivity to multiculturalism and their stances on the job debate. For its analytical methodology, this study proposes an analytical approach that combines survey data from questionnaires with machine-learning algorithms. This study applies light gradient boosting machine (LightGBM) and SHapley Additive exPlanations (SHAP) to estimate the importance of the studied variables and interpret the estimate results. According to the results of this study, contact, rapport, experience, and familiarity with other cultures promoted receptivity, but competition over job opportunities led to realistic threats. |
format | Online Article Text |
id | pubmed-9420350 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-94203502022-08-29 An analysis of Koreans' attitudes towards migrants by application of algorithmic approaches Han, Seungwoo Heliyon Research Article Exclusivist behaviours toward migrants manifest not only from poor receptivity to multiculturalism, but also from competition for resources and opportunities such as job opportunities. This study analyses the socio-economic background of Koreans by categorizing them in terms of their receptivity to multiculturalism and their stances on the job debate. For its analytical methodology, this study proposes an analytical approach that combines survey data from questionnaires with machine-learning algorithms. This study applies light gradient boosting machine (LightGBM) and SHapley Additive exPlanations (SHAP) to estimate the importance of the studied variables and interpret the estimate results. According to the results of this study, contact, rapport, experience, and familiarity with other cultures promoted receptivity, but competition over job opportunities led to realistic threats. Elsevier 2022-08-12 /pmc/articles/PMC9420350/ /pubmed/36042735 http://dx.doi.org/10.1016/j.heliyon.2022.e10087 Text en © 2022 The Author(s) https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Research Article Han, Seungwoo An analysis of Koreans' attitudes towards migrants by application of algorithmic approaches |
title | An analysis of Koreans' attitudes towards migrants by application of algorithmic approaches |
title_full | An analysis of Koreans' attitudes towards migrants by application of algorithmic approaches |
title_fullStr | An analysis of Koreans' attitudes towards migrants by application of algorithmic approaches |
title_full_unstemmed | An analysis of Koreans' attitudes towards migrants by application of algorithmic approaches |
title_short | An analysis of Koreans' attitudes towards migrants by application of algorithmic approaches |
title_sort | analysis of koreans' attitudes towards migrants by application of algorithmic approaches |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9420350/ https://www.ncbi.nlm.nih.gov/pubmed/36042735 http://dx.doi.org/10.1016/j.heliyon.2022.e10087 |
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