Sentiment Analysis of Product Reviews in Russian using Convolutional Neural Networks

被引：23
|
作者：
Smetanin, Sergey [1 ]
Komarov, Mikhail [1 ]
机构：
[1] Natl Res Univ Higher Sch Econ, Moscow, Russia
来源：
2019 IEEE 21ST CONFERENCE ON BUSINESS INFORMATICS (CBI), VOL 1 | 2019年
关键词：
sentiment analysis; product reviews; neural networks; convolutional neural networks; word embeddings; natural language processing;
D O I：
10.1109/CBI.2019.00062
中图分类号：
F [经济];
学科分类号：
02 ;
摘要：
Nowadays, product reviews on e-commerce sites tend to be a valuable resource in terms of evaluation of customers' behavior, their preferences, and needs. This paper provides an approach for sentiment analysis of product reviews in Russian using convolutional neural networks. We use Word2Vec pre-trained vectors as inputs for neural networks. This approach utilizes no hand-crafted features or sentiment lexicons. The training dataset was collected from reviews on top-ranked goods from the major e-commerce site in Russia, where the user-ranked scores were used as class labels. The system demonstrated the F-measure score up to 75.45% in a three-class classification. The collected training dataset and word embeddings are available to the research community.
引用
收藏
页码：482 / 486
页数：5
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