Haiting Wang
ABSTRACT
With the vigorous development of e-commerce, reviews of online commodity has become an important data source for enterprises to improve the quality of goods and service. These comments contain the emotional tendencies of users on all aspects of a product. By performing a sentiment analysis of it, can not only help sellers understand the advantages and disadvantages of their products, but also provide data support for potential buyers'purchase decisions. This paper presents a new method of commodity attribute clustering based on combination neural networks. and the sentiment analysis of commodity reviews based on Word2vec, through Word2vec computing semantic similarity, establishing sentiment dictionary and using affective Dictionary to classify the test text. The experiment proves the validity and accuracy of the method in the Internet product reviews.
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