Sentiment Analysis in Spanish for Improvement of Products and Services: A Deep Learning Approach

被引:28
|
作者
Andres Paredes-Valverde, Mario [1 ]
Colomo-Palacios, Ricardo [2 ]
del Pilar Salas-Zarate, Maria [1 ]
Valencia-Garcia, Rafael [1 ]
机构
[1] Univ Murcia, Dept Informat & Sistemas, E-30100 Murcia, Spain
[2] Ostfold Univ Coll, Comp Sci Dept, Holden, Norway
关键词
CLASSIFICATION;
D O I
10.1155/2017/1329281
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
Sentiment analysis is an important area that allows knowing public opinion of the users about several aspects. This information helps organizations to know customer satisfaction. Social networks such as Twitter are important information channels because information in real time can be obtained and processed from them. In this sense, we propose a deep-learning-based approach that allows companies and organizations to detect opportunities for improving the quality of their products or services through sentiment analysis. This approach is based on convolutional neural network (CNN) and word2vec. To determine the effectiveness of this approach for classifying tweets, we conducted experiments with different sizes of a Twitter corpus composed of 100000 tweets. We obtained encouraging results with a precision of 88.7%, a recall of 88.7%, and an F-measure of 88.7% considering the complete dataset.
引用
收藏
页数:6
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