Pattern-based automatic induction of domain adapted resources for social media analysis
In this dissertation, we analyze different aspects of the language used in texts published along different social media, and we propose a set of methods for the automatic extraction of polar adjectives as well as for the automatic classification of these texts. First of all, we propose a new classif...
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| Tipo de recurso: | tesis doctoral |
| Estado: | Versión publicada |
| Fecha de publicación: | 2016 |
| País: | España |
| Institución: | CBUC, CESCA |
| Repositorio: | TDR. Tesis Doctorales en Red |
| OAI Identifier: | oai:www.tdx.cat:10803/350801 |
| Acceso en línea: | http://hdl.handle.net/10803/350801 |
| Access Level: | acceso abierto |
| Palabra clave: | Natural language processing Computational linguistics Language resources Sentiment analysis Opinion mining Social media analysis Applied linguistics Procesamiento del lenguaje natural Lingüística computacional Recursos lingüísticos Análisis de sentimiento Minería de opinión Análisis de medios sociales Lingüística aplicada Processament del llenguatge natural Recursos lingüístics Anàlisi del sentiment Mineria d'opinió Anàlisi de mitjans socials 004 81 |
| Sumario: | In this dissertation, we analyze different aspects of the language used in texts published along different social media, and we propose a set of methods for the automatic extraction of polar adjectives as well as for the automatic classification of these texts. First of all, we propose a new classification of polar adjectives according to their lexical features, based on a case study. Secondly, we implement a new domain adaptable system for the automatic extraction of polar adjectives (along with their polarity values), reducing the use of external language resources. Finally, we propose two automatic classifiers (one rule-based and one based on Decision Trees) to identify documents belonging to different stages of the purchase process and texts that analyze different aspects of the product. |
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