An analysis of Koreans' attitudes towards migrants by application of algorithmic approaches

Han, Seungwoo

doi:10.1016/j.heliyon.2022.e10087

Cited by 4 publications

(6 citation statements)

References 81 publications

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“…In this study, we used XAI to predict occupational fatality risk for migrant workers and interpret the results. Several previous studies used XAI for disease detection [ 45 ] and prediction [ 48 ], and to interpret results [ 69 ]. The findings validated that the XAI method aids in the interpretation of contextual factors related to occupational injuries among migrant workers.…”

Section: Discussionmentioning

confidence: 99%

Characteristics of fatal occupational injuries in migrant workers in South Korea: A machine learning study

Lee,

Cho

2023

Heliyon

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Section: Discussionmentioning

confidence: 99%

Characteristics of fatal occupational injuries in migrant workers in South Korea: A machine learning study

Lee,

Cho

2023

Heliyon

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“…Networking among immigrants cannot exist in isolation, and it is facilitated by the friendlier attitudes of native Koreans toward immigrants. By virtue of South Korea's cultural structure, xenophobia is less prevalent and immigrants are warmly welcomed (Han, 2022). Without this welcoming attitude, networking with migrants would be undesirable.…”

Section: Employment Success and Social Networkingmentioning

confidence: 99%

“…The economic policy of Sri Lanka considers women's migration to the Middle East as a potential means of boosting the country's gross national product three to four decades ago, but men's migration to South Korea now holds a prominent position in terms of its social impact and relatively high level of forex earnings (Han, 2022;Silva & Udayanga, 2018). The migration trend has moved from the Middle East to South Korea, and from women to men (Shaw, 2010).…”

Section: Introductionmentioning

confidence: 99%

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Social networking and subjective well-being among Sri Lankan youth immigrants in South Korea

Udayanga,

Chamathya,

Perera

2023

UCR

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Labor migration is often seen as a means to offer economic stability to prospective migrants, especially in developing countries. However, the desire for migration becomes less favorable in the absence of the supportive framework fostered by social networks among immigrants. Sri Lankan youth from rural areas who frequently experience financial hardships are being encouraged to migrate to South Korea. This article investigates how social networking influences the subjective well-being of those Sri Lankan labor immigrants in South Korea. In-depth interviews, case studies, and the retrieval of social media data were used to collect data. According to the analysis, the capacity for social networking influences the outcomes of migration. In addition, migration to South Korea has been promoted not as an alternative to existing financial stability solutions, but as a mainstream strategy for enhancing life satisfaction, particularly for young rural men in Sri Lanka. In addition, it is discovered that the host country must provide an environment conducive to the operation of migrant networks. Overall, the article demonstrates that having access to migrant networks is a fundamental element in ensuring the well-being of immigrants.

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“…(21) Las técnicas de minería de datos y el reconocimiento de patrones, aplicados mediante algoritmos supervisado y no supervisados, son ampliamente usados en este contexto. (22,23,24,25) Sin embargo, en la Superintendencia Nacional de Migraciones, desconoce su uso y los aportes que pueden generar para la toma de decisiones de los inspectores migratorios, a partir de la formación y visualización de agrupaciones o clústeres de datos similares que descubren el comportamiento de extranjeros en estado de calidad irregular, (26) y en base a ello, afronten la decisión de entregar una situación migratoria acertada.…”

Section: Introductionunclassified

Algoritmo no supervisado para clasificar niveles de riesgo de inmigración

Valles-Coral,

Lazo-Bartra,

Pinedo

et al. 2023

Data and Metadata

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Introducción: la migración es un fenómeno social que afecta la estructura y distribución de la población, siendo motivada por la búsqueda de mejores oportunidades y condiciones de vida. En tal sentido, la migración irregular representa un desafío para los países receptores, dado que conlleva la entrada de individuos sin la documentación correspondiente, pudiendo comprometer la seguridad nacional y el control fronterizo de los países.Objetivo: evaluar la aplicación del algoritmo no supervisado DBSCAN para clasificar a extranjeros según el nivel de riesgo de inmigración irregular en la Superintendencia Nacional de Migraciones del Perú.Métodos: empleamos el algoritmo DBSCAN sobre un dataset proveniente de la Superintendencia Nacional de Migraciones, clasificando a extranjeros en clústeres según su nivel de riesgo de inmigración irregular, además, usamos los coeficientes de Silhouette, Davies-Bouldin, y Calinski-Harabasz para evaluar la calidad de la clasificación.Resultados: DBSCAN clasificó a los extranjeros en cuatro clústeres según el nivel de riesgo de inmigración irregular: alto, medio alto, medio bajo y bajo, donde el desempeño del índice Silhouette fue de 0.5338, el desempeño del índice Davies-Bouldin fue 0.6213 y el desempeño del índice Calinski-Harabasz fue 3680.2359.Conclusiones: evidenciamos que el uso de DBSCAN en la Superintendencia Nacional de Migraciones clasificó eficazmente a extranjeros según el nivel de riesgo de inmigración irregular, esta herramienta respalda decisiones informadas de inspectores migratorios, favoreciendo la regulación migratoria peruana.

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An analysis of Koreans' attitudes towards migrants by application of algorithmic approaches

Cited by 4 publications

References 81 publications

Characteristics of fatal occupational injuries in migrant workers in South Korea: A machine learning study

Characteristics of fatal occupational injuries in migrant workers in South Korea: A machine learning study

Social networking and subjective well-being among Sri Lankan youth immigrants in South Korea

Algoritmo no supervisado para clasificar niveles de riesgo de inmigración

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