EmotiBloga fine-grained annotation schema for labelling subjectivity in the new-textual genres born with the Web 2.0

  1. Boldrini, Ester
  2. Balahur Dobrescu, Alexandra
  3. Martínez Barco, Patricio
  4. Montoyo Guijarro, Andrés
Revista:
Procesamiento del lenguaje natural

ISSN: 1135-5948

Año de publicación: 2010

Número: 45

Páginas: 41-48

Tipo: Artículo

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Otras publicaciones en: Procesamiento del lenguaje natural

Resumen

El crecimiento exponencial de la información subjetiva en el marco de la Web 2.0 ha creado la necesidad de producir herramientas de Procesamiento del Lenguaje Natural que sean capaces de analizar y procesar estos datos para aplicaciones concretas. Estas herramientas requieren un entrenamiento con corpus anotados con este tipo de información a nivel muy detallado para poder capturar aquellos fenómenos lingüísticos que contienen una carga emotiva. El presente artículo describe EmotiBlog, un modelo detallado para la anotación de la subjetividad. Presentamos el proceso de creación y demostramos que aporta mejoras a los sistemas de aprendizaje automático. Para ello, empleamos distintos corpus que presentan textos de diversos géneros – una colección de noticias periodísticas en estilo indirecto, la colección de títulos de noticias anotados con la polaridad y emoción del SemEval 2007 (Tarea 14) e ISEAR, un corpus de expresiones reales de emociones. Además, demostramos que otros recursos pueden integrarse con EmotiBlog. Los resultados prueban que gracias a su estructura y parámetros de anotación, el modelo propuesto, EmotiBlog, proporciona ventajas considerables para el entrenamiento de sistemas que trabajan con minería de opiniones y detección de emoción.

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Fuente de los datos: Dialnet