Examinando por Materia "K-Means"

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    Ítem
    Estudio de la relación entre los valores sociales y la aceptación de sobornos como conducta corrupta : un estudio con modelos SEM y datos de la encuesta mundial de valores
    (Universidad EAFIT, 2024) Gómez Convers, Giovanny Hernando; Castrillón-Orrego, Sergio A.; Almonacid Hurtado, Paula María
    In a global context of rapid social change, investigating the relationship between social values and corruption has become increasingly urgent and significant. Which behaviors are desirable? Which do we manifest in daily life? The World Values Survey (WVS) serves as a crucial data source for understanding social values in various contexts. However, how these values influence the acceptance of bribery, and thus corruption, has not been sufficiently explored. This study examines the underlying patterns in response clusters and systematically analyzes them using the holistic possibilities offered by the institutionalism theoretical framework. The objective is to identify the most significant causalities and influences in the relationship between social values and corruption. Through robust data analysis, imputation techniques, dimensionality reduction, clustering analysis, and SEM modeling, we identify the main factors impacting the acceptance of bribery. The results demonstrate that the three pillars of institutionalism provide a valuable approach to understanding corruption by simultaneously considering key variables and components. When internalized, social values facilitate the acceptance of bribery in certain contexts, highlighting the influence of the cognitive dimension. Although legal frameworks can enhance transparency, cultural environment and customs have a more determining influence on the acceptance of corrupt practices. These findings underscore the need to foster a strong ethical culture and implement educational programs that promote integrity and transparency to effectively mitigate corruption.
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    Segmentación de los flujos migratorios en Colombia : identificación de subgrupos y características comunes
    (Universidad EAFIT, 2024) Aguirre Marín, Cindy Vanessa; Martínez Vargas, Juan David; Sepúlveda Cano, Lina María
    The increase in global migration has intensified migratory flows, emerging as a relevant phenomenon for global, regional, and national policies. In Colombia, since 2015, Venezuelan migration has sparked interest in migratory flows. This study analyzes migratory flows to Colombia in 2023 using Machine Learning techniques. K-Means was applied in order to segment data from Migration Colombia, while UMAP was used to reduce the dimensionality of the data itself. The results reveal four main clusters, defined by the region of origin, reason for travel, host region, and month of arrival. Most flows correspond to tourists, suggesting that the data from official migration points primarily reflect tourist movements and not necessarily other types of migration. Machine Learning techniques proved effective in uncovering complex patterns in categorical data, and interpretation using SmartExplainer by SHAPash facilitated the understanding of these patterns. This study not only adequately segmented migratory flows but also provided interpretative tools for future analyses of categorical data.