Evaluation of potential Spanish text markers on social posts asfeatures for polarity classification
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| Autores: | , , |
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| Formato: | artículo original |
| Fecha de Publicación: | 2017 |
| Descripción: | This work describes the identification and evaluation process of potential text markers for sen-timent analysis. Evaluation of the markers and its use as part of the feature extraction processfrom plain text that is needed for sentiment analysis is presented. Evaluation of text markerobtained as a result of systematic analysis from a corpus over a second one allowed us to iden-tify that emphasized positive words are strong indicators for positive text. The second corpusallowed us to evaluate the relation between the polarity of emphasized words and the text theyappear in. Evaluation of the markers for polarity detection task in combination with a polarizeddictionary produced polarity classification average precision of 56% using only three markers.This are promising results compared to the top 69% obtained using more features and specializeddictionaries for the same task |
| País: | Kérwá |
| Institución: | Universidad de Costa Rica |
| Repositorio: | Kérwá |
| OAI Identifier: | oai:kerwa.ucr.ac.cr:10669/79876 |
| Acceso en línea: | http://www.clei.org/cleiej/index.php/cleiej/article/view/11 https://hdl.handle.net/10669/79876 |
| Palabra clave: | Information retrieval Natural language processing Sentiment analysis Feature vectors Text classification |