Supervised polarity classification of Spanish tweets based on linguistic knowledge
Title
Supervised polarity classification of Spanish tweets based on linguistic knowledgeDate
2013Citation
David Vilares, Miguel Ángel Alonso, and Carlos Gómez-Rodríguez. 2013. Supervised polarity classification of Spanish tweets based on linguistic knowledge. In Proceedings of the 2013 ACM symposium on Document engineering (DocEng '13). Association for Computing Machinery, New York, NY, USA, 169–172. https://doi.org/10.1145/2494266.2494300
Abstract
[Abstract]: We describe a system that classifies the polarity of Spanish tweets. We adopt a hybrid approach, which combines machine learning and linguistic knowledge acquired by means of NLP. We use part-of-speech tags, syntactic dependencies and semantic knowledge as features for a supervised classifier. Lexical particularities of the language used in Twitter are taken into account in a pre-processing step. Experimental results improve over those of pure machine learning approaches and confirm the practical utility of the proposal.
Keywords
Document Analysis
Linguistic Analysis
Machine Learning
Opinion Mining
Sentiment Analysis
Twitter
Linguistic Analysis
Machine Learning
Opinion Mining
Sentiment Analysis
Description
This is the author's version of the work. It is posted here for your personal use. Not for redistribution. The definitive Version of Record was published in Proceedings of the 2013 ACM symposium on Document engineering (DocEng '13). Association for Computing Machinery, New York, NY, USA, 169–172. https://doi.org/10.1145/2494266.2494300.
Editor version
Rights
Todos os dereitos reservados. All rights reserved.
ISBN
978-1-4503-1789-4