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Comenzamos a calentar los motores para la celebración de los 40 años del GSI. Hoy traigo uno de los primeros artículos del grupo en nuestro tema: "Inteligencia Artificial" publicado por Gregorio en el BIT del CO ...

Este martes 24 de junio se presentan los resultados del proyecto AMOR en Aranjuez en el curso de verano de la URJC organizado por CETINIA titulado "Human-centred Artificial Intelligence: How to bypass the Turing Tra ...

Hoy 12/12/2024 se presenta el proyecto AMOR en el UNICO I+D Project Meet-up Madrid organizado por el proyecto ELADAIS con la participación de los proyectos UNICO CLOUD financiados en la UPM (ELADAIS, MAP 6G, RISC ...

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The journal paper An Approach for Radicalization Detection based on Emotion Signals and Semantic Similarity by Oscar Araque and Carlos Angel Iglesias has been published at IEEE Access (4.098 impact factor, Q1 JCR-2018).

The paper is available at the following URL: https://ieeexplore.ieee.org/document/8962050

DOI: https://doi.org/10.1109/ACCESS.2020.2967219

 

Abstract:

The Internet has become an important tool for modern terrorist groups as a means of spreading their propaganda messages and recruitment purposes. Previous studies have shown that the analysis of social signs can help in the analysis, detection, and prediction of radical users. In this work, we focus on the analysis of affect signs in social media and social networks, which has not been yet previously addressed. The article contributions are: (i) a novel dataset to be used in radicalization detection works, (ii) a method for utilizing an emotion lexicon for radicalization detection, and (iii) an application to the radical detection domain of an embedding-based semantic similarity model. Results show that emotion can be a reliable indicator of radicalization, as well as that the proposed feature extraction methods can yield high-performance scores.