Research on Sentiment Classification Algorithms on Online Review

The product online review text contains a large number of opinions and emotions. In order to identify the public’s emotional and tendentious information, we present reinforcement learning models in which sentiment classification algorithms of product online review corpus are discussed in this paper....

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Bibliographic Details
Published in:Complexity (New York, N.Y.) N.Y.), 2020, Vol.2020 (2020), p.1-6
Main Authors: Wang, Xiaoli, Xie, Yanxi, Xia, Zhijie, Yan, Ruixia, Song, Zukang
Format: Article
Language:English
Subjects:
Algorithms
Artificial intelligence
Classification
Deep learning
Emotions
Machine learning
Natural language processing
Neural networks
Semantics
Sentiment analysis
Support vector machines
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Summary:The product online review text contains a large number of opinions and emotions. In order to identify the public’s emotional and tendentious information, we present reinforcement learning models in which sentiment classification algorithms of product online review corpus are discussed in this paper. In order to explore the classification effect of different sentiment classification algorithms, we conducted a research on Naive Bayesian algorithm, support vector machine algorithm, and neural network algorithm and carried out some comparison using a concrete example. The evaluation indexes and the three algorithms are compared in different lengths of sentence and word vector dimensions. The results present that neural network algorithm is effective in the sentiment classification of product online review corpus.
ISSN:1076-2787
1099-0526
DOI:10.1155/2020/5093620