Analysis of Factors Influencing the Trust Levels of Kyrgyzstan Residents, Using Neural Network Analysis
Autor(a) principal: | |
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Data de Publicação: | 2023 |
Tipo de documento: | Artigo |
Idioma: | eng por |
Título da fonte: | Encontros Bibli |
Texto Completo: | https://periodicos.ufsc.br/index.php/eb/article/view/93526 |
Resumo: | Objective: Kyrgyzstan, located in Central Asia, is a country which has a strong will to achieve national development. The aim of this study is to measure the levels of trust of local residents, a highly important factor in national development, and to derive suggestions for improving it. To this end, the primary means employed is to target the residents of Kyrgyzstan and measure the levels of trust they have towards each other. Methods: The study uses data relating to aid projects for rural development that Korea’s Good Neighbors International organization (GNI) is jointly carrying out in Kyrgyzstan along with the Korea International Cooperation Agency (KOICA), a Korean aid provider. In order to carry out the aid project to Kyrgyzstan, these organizations conducted a baseline survey at the initial stage, and the results of this study were used for analysis. As regards the analytical method used in this study, neural network analysis was employed for the questionnaire survey data of 583 people in Kyrgyzstan that was used for the baseline survey. Results: Neural network analysis, a component of the big data analysis method, has recently been in the academic limelight. The analysis revealed that ethnicity had the greatest influence on the trust levels of Kyrgyzstan residents, followed by gender and education level, in that order. Conclusions: From this, it can be seen that multifaceted efforts are needed to increase the levels of trust of peoples other than ethnic Kyrgyzstanis, as they occupy a central position in Kyrgyzstan. |
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Analysis of Factors Influencing the Trust Levels of Kyrgyzstan Residents, Using Neural Network Analysis Análisis de los factores que influyen en los niveles de confianza de los residentes de Kirguistán mediante el análisis de redes neuronalesAnálise dos fatores que influenciam os níveis de confiança dos residentes do Quirguistão, usando análise de rede neuralKyrgyz ODATrustNeural network analysis Kirguistán ODAConfianzaAnálisis de redes neuronalesQuirguistão ODAConfiançaAnálise de redes neuraisObjective: Kyrgyzstan, located in Central Asia, is a country which has a strong will to achieve national development. The aim of this study is to measure the levels of trust of local residents, a highly important factor in national development, and to derive suggestions for improving it. To this end, the primary means employed is to target the residents of Kyrgyzstan and measure the levels of trust they have towards each other. Methods: The study uses data relating to aid projects for rural development that Korea’s Good Neighbors International organization (GNI) is jointly carrying out in Kyrgyzstan along with the Korea International Cooperation Agency (KOICA), a Korean aid provider. In order to carry out the aid project to Kyrgyzstan, these organizations conducted a baseline survey at the initial stage, and the results of this study were used for analysis. As regards the analytical method used in this study, neural network analysis was employed for the questionnaire survey data of 583 people in Kyrgyzstan that was used for the baseline survey. Results: Neural network analysis, a component of the big data analysis method, has recently been in the academic limelight. The analysis revealed that ethnicity had the greatest influence on the trust levels of Kyrgyzstan residents, followed by gender and education level, in that order. Conclusions: From this, it can be seen that multifaceted efforts are needed to increase the levels of trust of peoples other than ethnic Kyrgyzstanis, as they occupy a central position in Kyrgyzstan.Objetivo: Kirguistán, ubicado en Asia Central, es un país que tiene una fuerte voluntad de lograr el desarrollo nacional. El objetivo de este estudio es medir los niveles de confianza de los pobladores locales, factor de gran importancia para el desarrollo nacional, y presentar sugerencias para su mejora. Con ese fin, el principal medio empleado es llegar a los residentes de Kirguistán y medir los niveles de confianza que tienen entre sí. Método: el estudio utiliza datos relacionados con proyectos de ayuda para el desarrollo rural que la Organización Internacional de Buenos Vecinos de Corea (GNI) está llevando a cabo conjuntamente en Kirguistán, junto con la Agencia de Cooperación Internacional de Corea (KOICA), un proveedor de ayuda coreana. Para llevar a cabo el proyecto de ayuda para Kirguistán, estas organizaciones llevaron a cabo una investigación de referencia en la fase inicial, y los resultados de este estudio se utilizaron para el análisis. Con respecto al método analítico utilizado en este estudio, se empleó el análisis de redes neuronales para los datos de la encuesta del cuestionario de 583 personas en Kirguistán, que se utilizó para la encuesta de referencia. Resultados: el análisis de redes neuronales, un componente del método de análisis de big data, ha estado recientemente en el centro de atención académico. El análisis reveló que el origen étnico tenía la mayor influencia en los niveles de confianza de los residentes de Kirguistán, seguido por el género y el nivel educativo, en ese orden. Conclusiones: a partir de esto se evidencia que se necesitan esfuerzos multifacéticos para aumentar los niveles de confianza de las personas que no son de etnia kirguisa, ya que ocupan una posición central en Kirguistán.Objetivo: O Quirguistão, localizado na Ásia Central, é um país que tem uma forte vontade de alcançar o desenvolvimento nacional. O objetivo deste estudo é medir os níveis de confiança dos residentes locais, fator de grande importância para o desenvolvimento nacional, e apresentar sugestões para a sua melhoria. Para esse fim, o principal meio empregado é atingir os residentes do Quirguistão e medir os níveis de confiança que eles têm uns nos outros. Método: O estudo usa dados relativos a projetos de ajuda para o desenvolvimento rural que a Organização Internacional de Bons Vizinhos da Coréia (GNI) está realizando em conjunto no Quirguistão, juntamente com a Agência de Cooperação Internacional da Coréia (KOICA), um provedor de ajuda coreana. Para realizar o projeto de ajuda ao Quirguistão, essas organizações realizaram uma pesquisa de base na fase inicial, e os resultados desse estudo foram usados para análise. No que diz respeito ao método analítico usado neste estudo, a análise de redes neurais foi empregada para os dados da pesquisa por questionário de 583 pessoas no Quirguistão, que foi usada para a pesquisa de linha de base. Resultados: A análise de redes neurais, um componente do método de análise de big data, tem estado recentemente no centro das atenções acadêmicas. A análise revelou que a etnia teve a maior influência nos níveis de confiança dos residentes do Quirguistão, seguida por gênero e nível educacional, nessa ordem. Conclusões: A partir disso, pode-se ver que são necessários esforços multifacetados para aumentar os níveis de confiança de pessoas que não são de etnia quirguiz, pois ocupam uma posição central no Quirguistão.Departamento de Ciência da Informação – UFSC2023-05-17info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfapplication/pdfapplication/pdfhttps://periodicos.ufsc.br/index.php/eb/article/view/9352610.5007/1518-2924.2023.e93526Encontros Bibli: revista eletrônica de biblioteconomia e ciência da informação; Vol. 28 (2023): Innovation, Technology and Sustainability; 1-17Encontros Bibli: revista electrónica de bibliotecología y ciencias de la información.; Vol. 28 (2023): Innovación, Tecnología y Sustentabilidad; 1-17Encontros Bibli: revista eletrônica de biblioteconomia e ciência da informação; v. 28 (2023): Inovação, Tecnologia e Sustentabilidade; 1-171518-2924reponame:Encontros Bibliinstname:Universidade Federal de Santa Catarina (UFSC)instacron:UFSCengporhttps://periodicos.ufsc.br/index.php/eb/article/view/93526/53229https://periodicos.ufsc.br/index.php/eb/article/view/93526/53225https://periodicos.ufsc.br/index.php/eb/article/view/93526/53226Copyright (c) 2023 Young-Chool Choihttps://creativecommons.org/licenses/by/4.0info:eu-repo/semantics/openAccessChoi, Young-Chool2023-11-15T12:31:13Zoai:periodicos.ufsc.br:article/93526Revistahttps://periodicos.ufsc.br/index.php/eb/indexPUBhttps://periodicos.ufsc.br/index.php/eb/oaiencontrosbibli@contato.ufsc.br||portaldeperiodicos.bu@contato.ufsc.br1518-29241518-2924opendoar:2023-11-15T12:31:13Encontros Bibli - Universidade Federal de Santa Catarina (UFSC)false |
dc.title.none.fl_str_mv |
Analysis of Factors Influencing the Trust Levels of Kyrgyzstan Residents, Using Neural Network Analysis Análisis de los factores que influyen en los niveles de confianza de los residentes de Kirguistán mediante el análisis de redes neuronales Análise dos fatores que influenciam os níveis de confiança dos residentes do Quirguistão, usando análise de rede neural |
title |
Analysis of Factors Influencing the Trust Levels of Kyrgyzstan Residents, Using Neural Network Analysis |
spellingShingle |
Analysis of Factors Influencing the Trust Levels of Kyrgyzstan Residents, Using Neural Network Analysis Choi, Young-Chool Kyrgyz ODA Trust Neural network analysis Kirguistán ODA Confianza Análisis de redes neuronales Quirguistão ODA Confiança Análise de redes neurais |
title_short |
Analysis of Factors Influencing the Trust Levels of Kyrgyzstan Residents, Using Neural Network Analysis |
title_full |
Analysis of Factors Influencing the Trust Levels of Kyrgyzstan Residents, Using Neural Network Analysis |
title_fullStr |
Analysis of Factors Influencing the Trust Levels of Kyrgyzstan Residents, Using Neural Network Analysis |
title_full_unstemmed |
Analysis of Factors Influencing the Trust Levels of Kyrgyzstan Residents, Using Neural Network Analysis |
title_sort |
Analysis of Factors Influencing the Trust Levels of Kyrgyzstan Residents, Using Neural Network Analysis |
author |
Choi, Young-Chool |
author_facet |
Choi, Young-Chool |
author_role |
author |
dc.contributor.author.fl_str_mv |
Choi, Young-Chool |
dc.subject.por.fl_str_mv |
Kyrgyz ODA Trust Neural network analysis Kirguistán ODA Confianza Análisis de redes neuronales Quirguistão ODA Confiança Análise de redes neurais |
topic |
Kyrgyz ODA Trust Neural network analysis Kirguistán ODA Confianza Análisis de redes neuronales Quirguistão ODA Confiança Análise de redes neurais |
description |
Objective: Kyrgyzstan, located in Central Asia, is a country which has a strong will to achieve national development. The aim of this study is to measure the levels of trust of local residents, a highly important factor in national development, and to derive suggestions for improving it. To this end, the primary means employed is to target the residents of Kyrgyzstan and measure the levels of trust they have towards each other. Methods: The study uses data relating to aid projects for rural development that Korea’s Good Neighbors International organization (GNI) is jointly carrying out in Kyrgyzstan along with the Korea International Cooperation Agency (KOICA), a Korean aid provider. In order to carry out the aid project to Kyrgyzstan, these organizations conducted a baseline survey at the initial stage, and the results of this study were used for analysis. As regards the analytical method used in this study, neural network analysis was employed for the questionnaire survey data of 583 people in Kyrgyzstan that was used for the baseline survey. Results: Neural network analysis, a component of the big data analysis method, has recently been in the academic limelight. The analysis revealed that ethnicity had the greatest influence on the trust levels of Kyrgyzstan residents, followed by gender and education level, in that order. Conclusions: From this, it can be seen that multifaceted efforts are needed to increase the levels of trust of peoples other than ethnic Kyrgyzstanis, as they occupy a central position in Kyrgyzstan. |
publishDate |
2023 |
dc.date.none.fl_str_mv |
2023-05-17 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://periodicos.ufsc.br/index.php/eb/article/view/93526 10.5007/1518-2924.2023.e93526 |
url |
https://periodicos.ufsc.br/index.php/eb/article/view/93526 |
identifier_str_mv |
10.5007/1518-2924.2023.e93526 |
dc.language.iso.fl_str_mv |
eng por |
language |
eng por |
dc.relation.none.fl_str_mv |
https://periodicos.ufsc.br/index.php/eb/article/view/93526/53229 https://periodicos.ufsc.br/index.php/eb/article/view/93526/53225 https://periodicos.ufsc.br/index.php/eb/article/view/93526/53226 |
dc.rights.driver.fl_str_mv |
Copyright (c) 2023 Young-Chool Choi https://creativecommons.org/licenses/by/4.0 info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
Copyright (c) 2023 Young-Chool Choi https://creativecommons.org/licenses/by/4.0 |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf application/pdf application/pdf |
dc.publisher.none.fl_str_mv |
Departamento de Ciência da Informação – UFSC |
publisher.none.fl_str_mv |
Departamento de Ciência da Informação – UFSC |
dc.source.none.fl_str_mv |
Encontros Bibli: revista eletrônica de biblioteconomia e ciência da informação; Vol. 28 (2023): Innovation, Technology and Sustainability; 1-17 Encontros Bibli: revista electrónica de bibliotecología y ciencias de la información.; Vol. 28 (2023): Innovación, Tecnología y Sustentabilidad; 1-17 Encontros Bibli: revista eletrônica de biblioteconomia e ciência da informação; v. 28 (2023): Inovação, Tecnologia e Sustentabilidade; 1-17 1518-2924 reponame:Encontros Bibli instname:Universidade Federal de Santa Catarina (UFSC) instacron:UFSC |
instname_str |
Universidade Federal de Santa Catarina (UFSC) |
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UFSC |
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UFSC |
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Encontros Bibli |
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Encontros Bibli |
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Encontros Bibli - Universidade Federal de Santa Catarina (UFSC) |
repository.mail.fl_str_mv |
encontrosbibli@contato.ufsc.br||portaldeperiodicos.bu@contato.ufsc.br |
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