Sentiment classification in English from sentence-levelannotations of emotions regarding models of affect
This paper presents a text classifier for automatically taggingthe sentiment of input text according to the emotion that is beingconveyed. This system has a pipelined framework composedof Natural Language Processing modules for feature extractionand a hard binary classifier for decision making betwe...
| Autores: | , |
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| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2009 |
| País: | España |
| Institución: | Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya) |
| Repositorio: | Recercat. Dipósit de la Recerca de Catalunya |
| OAI Identifier: | oai:recercat.cat:20.500.14342/2876 |
| Acceso en línea: | http://hdl.handle.net/20.500.14342/2876 |
| Access Level: | acceso abierto |
| Palabra clave: | Parla Processament de la parla |
| Sumario: | This paper presents a text classifier for automatically taggingthe sentiment of input text according to the emotion that is beingconveyed. This system has a pipelined framework composedof Natural Language Processing modules for feature extractionand a hard binary classifier for decision making between posi-tive and negative categories. To do so, the Semeval 2007 datasetcomposed of sentences emotionally annotated is used for train-ing purposes after being mapped into a model of affect. Theresulting scheme stands a first step towards a complete emotionclassifier for a future automatic expressive text-to-speech syn-thesizer. |
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