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The media framing dataset: Analyzing news narratives in Mexico and Colombia
(2025-01-09) Cuadrado, Juan; Martinez, Elizabeth; Puertas, Edwin; Martinez-Santos, Juan Carlos
This paper introduces “The Media Framing Dataset,” a dataset developed through an in-depth examination of news articles from 140 local newspapers in Mexico and Colombia, covering events from May 2022 to August 2023. Our dataset captures a broad spectrum of topics, including politics, immigration, public opinion, and crime. The data collection involved a meticulous keyword-based search strategy designed to identify articles that illustrate various news-framing dimensions, such as Economics, Policy, Morality, and more.
To construct this dataset, we employed a combination of manual and automated annotation techniques. Articles were categorized based on specific framing dimensions using a structured framework, developed in collaboration with experts in computational linguistics. The annotation process, conducted by trained annotators from Mexicoʼs Delfin program, guarantees both precision and depth.
“The Media Framing Dataset” serves as a valuable resource for NLP research with high potential for reuse. It is particularly suitable for analyzing cultural and linguistic nuances in media framing, assessing the impact of framing on public perception, and supporting the development of models that automatically detect framing techniques. Additionally, it provides a foundation for linguistic analysis and machine learning projects, enabling researchers and practitioners to explore media framing dynamics and develop innovative tools for media analysis.
Adaptación de la escala de machismo sexual/sexismo (EMS-Sexismo-12) en una ciudad del Caribe colombiano
(2024-06-17) Pastrana Quintana, Camilo Andrés; Fortich Pérez, David Javier; Neira Salas, Jeison David; Ortega Mastrodomenico, Eliana Carolina; Ortega Mastrodomenico, Eliana Carolina
El objetivo del estudio fue adaptar y validar la escala de machismo sexual/sexismo (EMS-Sexismo-12) para población adulta de una ciudad del caribe colombiano. Participaron 678 individuos con edades entre los 18 a 79 años (M = 26.32; DE = 10.76; 50% mujeres) de la ciudad de Cartagena de indias, seleccionados con un muestreo no probabilístico. La escala presentó una buena adaptación al contexto, se utilizaron seis jueces en el Índice de coherencia entre jueces CVC de Hernández-Nieto (2002) de .936. El análisis factorial confirmatorio con el estimador máxima verosimilitud robusto mostró una estructura unifactorial con 10 ítems que presentaron adecuados índices de ajuste (CFI = .94, PNFI = .72, RMSEA = .04, [.041 - .057]). Coeficientes de fiabilidad superiores a .9 (Omega de McDonald y Alfa Ordinal). Siendo así, se presentan evidencias de validez contenido y constructo. Se concluye que las medidas obtenidas de la escala resultan válidas para la población bajo estudio.
Entorno, información y decisiones empresariales
(2024-10) Martínez Palomino, Oriana Susana
El entorno en el que operan los mercados se caracteriza por tener un alto grado de dinamismo, diversidad, complejidad y turbulencia. Como resultado, surgen una serie de factores y fuerzas externas que no solo afectan de manera positiva o negativa al desempeño de las organizaciones, sino que además las conduce a múltiples escenarios de actuación e interacción. Los desafíos que hoy se enfrentan, enmarcados en una realidad circundante efímera, son cada vez más inesperados e impredecibles. En un escenario de este tipo, los datos y la información se convierten en un insumo invaluable que favorece el proceso de toma de decisiones y una adecuada gestión del riesgo (y más si se tiene en cuenta la mayor facilidad que ofrece el creciente acceso a internet). No obstante, abordar y utilizar toda la información disponible mientras tratan de alcanzar un posicionamiento que responda a sus objetivos estratégicos puede ser también un reto mayúsculo para las empresas. A continuación, se describen algunas acciones clave que ayudan a enfrentar dichos desafíos.
Multifractal detrended cross-correlation coefficient for cosmic ray and sunspot time series
(2025-01-13) Sierra Porta, David
This study delves into the multifractal cross-correlations between cosmic ray intensity and sunspot numbers, addressing the shortcomings of traditional correlation analyses that often fail to capture the intricate and multifractal nature of these time series. Cosmic rays and solar activity are critical components of space weather dynamics, and understanding their interactions is essential for predicting space weather events that can affect satellite operations, communication systems, and even climate on Earth. We employ Multifractal Detrended Cross-Correlation Analysis (MFDCCA) to explore these complex relationships across a range of time scales. Our methodology involves segmenting the time series into windows of varying lengths, from 50 to 3900 days, and calculating cross-correlation coefficients for different polynomial fitting orders and fluctuation orders
, using polynomial orders of 2, 3, 4, and 5. This approach allows us to capture the multifractal properties and temporal dependencies within and between the series.
Our analysis reveals significant multifractal correlations, with the highest correlation coefficient of 0.876 occurring for
and polynomial order 2 with a lag of 57 days. The results demonstrate that higher polynomial orders result in more stable and robust coefficients, indicating stronger correlations on larger scales. These findings highlight the efficacy of advanced techniques like MFDCCA in uncovering the complex interactions between cosmic rays and solar activity, which are often missed by conventional methods. The implications of our study extend to the enhancement of space weather prediction models. By incorporating additional heliophysical variables such as solar wind conditions, interplanetary magnetic field data, and indices of coronal mass ejections or solar flares, future research can construct more comprehensive models that better capture the multifractal interactions governing these phenomena. This expanded understanding is crucial for improving the accuracy of space weather forecasts and mitigating the potential impacts of space weather events on technological and natural systems.
Network structure and urban mobility sustainability: A topological analysis of cities from the urban mobility readiness index
(2025-01-13) Herrera Acevedo, Daniel; Sierra Porta, David
In the context of rapid urbanization, efficient and sustainable urban mobility is critical. This study explores the impact of urban network structure and socio-demographic factors on Urban Mobility Readiness (UMRi) across 62 cities worldwide. Using complex network analysis, Principal Component Analysis, and multiple linear regression models, we identify significant relationships between network metrics — such as average node degree, clustering coefficient, and graph diameter — and urban mobility performance. Cities with denser, more interconnected networks tend to achieve higher UMRi scores, indicating better preparedness for modern mobility challenges.
Our findings also highlight the importance of economic resources, with GDP per capita emerging as a significant predictor of UMRi. Cities with well-funded and well-designed transportation networks demonstrate stronger performance in terms of mobility readiness and sustainability. Conversely, cities with more dispersed networks face greater challenges in optimizing their transportation systems. These insights underscore the importance of compact, resilient networks that promote accessibility and efficiency.
This study emphasizes the critical role of network structure in shaping urban mobility outcomes and offers strategic guidance for enhancing transportation systems in rapidly growing urban areas. Future research should focus on integrating emerging technologies, such as autonomous vehicles and smart city solutions, to further optimize urban mobility. This approach offers a novel perspective on how the structure of urban networks influences the sustainability and efficiency of public transport in diverse urban contexts.