Sentiment Groups as Features of a Classification Model Using a Spanish Sentiment Lexicon: A Hybrid Approach

被引：3

作者：

Gutierrez, Ernesto ^{[1
]}

Cervantes, Ofelia ^{[1
]}

Baez-Lopez, David ^{[1
]}

Alfredo Sanchez, J. ^{[1
]}

机构：

[1] Amer Univ, Cholula, Mexico

来源：

PATTERN RECOGNITION (MCPR 2015) | 2015年 / 9116卷

关键词：

Sentiment analysis; Opinion mining; Polarity identification; Spanish lexicon; Sentiment lexicon; Lexicon-based sentiment identification; Support vector machines; Classification model;

D O I：

10.1007/978-3-319-19264-2_25

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Discovering people's subjective opinion about a topic of interest has become more relevant with the explosion in the use of social networks, microblogs, forums and e-commerce pages all over the Internet. Sentiment analysis techniques aim to identify polarity of opinions by analyzing explicit and implicit features within the text. This paper presents a hybrid approach to extract features from Spanish sentiment sentences in order to create a model based on support vector machines and determine polarity of opinions. In addition to this, a Spanish Sentiment Lexicon has been constructed. Accuracy of the model is evaluated against two previously tagged corpora and results are discussed.

引用

页码：258 / 268

页数：11

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