| Revista: | Computación y sistemas |
| Base de datos: | |
| Número de sistema: | 000560358 |
| ISSN: | 1405-5546 |
| Autores: | Hercig, Tomáš1 Krejzl, Peter1 Král, Pavel1 |
| Instituciones: | 1University of West Bohemia, Faculty of Applied Sciences, Plzeň. República Checa |
| Año: | 2018 |
| Periodo: | Jul-Sep |
| Volumen: | 22 |
| Número: | 3 |
| Paginación: | 787-794 |
| País: | México |
| Idioma: | Inglés |
| Tipo de documento: | Artículo |
| Resumen en inglés | Sentiment analysis is a wide area with great potential and many research directions. One direction is stance detection, which is somewhat similar to sentiment analysis. We supplement stance detection dataset with sentiment annotation and explore the similarities of these tasks. We show that stance detection and sentiment analysis can be mutually beneficial by using gold label for one task as features for the other task. We analysed the presence of target entities for stance detection in the dataset. We outperform the state-of-the-art results for stance detection in Czech and set new state-of-the-art results for the newly created sentiment analysis part of the extended dataset. |
| Disciplinas: | Ciencias de la computación |
| Palabras clave: | Inteligencia artificial, Análisis de sentimientos, Detección de postura, Procesamiento de lenguaje natural, Redes neuronales convolucionales, Checo, Conjunto de datos |
| Keyword: | Convolutional neuronal networks, Natural language processing, Stance detection, Sentiment analysis, Czech, Artificial intelligence, Datasets |
| Texto completo: | Texto completo (Ver HTML) Texto completo (Ver PDF) |
