Research on Sentiment Classification Algorithms on Online Review
Joint Authors
Wang, Xiaoli
Yan, Ruixia
Xia, Zhijie
Xie, Yanxi
Song, Zukang
Source
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-6, 6 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-09-08
Country of Publication
Egypt
No. of Pages
6
Main Subjects
Abstract EN
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.
American Psychological Association (APA)
Yan, Ruixia& Xia, Zhijie& Xie, Yanxi& Wang, Xiaoli& Song, Zukang. 2020. Research on Sentiment Classification Algorithms on Online Review. Complexity،Vol. 2020, no. 2020, pp.1-6.
https://search.emarefa.net/detail/BIM-1142243
Modern Language Association (MLA)
Yan, Ruixia…[et al.]. Research on Sentiment Classification Algorithms on Online Review. Complexity No. 2020 (2020), pp.1-6.
https://search.emarefa.net/detail/BIM-1142243
American Medical Association (AMA)
Yan, Ruixia& Xia, Zhijie& Xie, Yanxi& Wang, Xiaoli& Song, Zukang. Research on Sentiment Classification Algorithms on Online Review. Complexity. 2020. Vol. 2020, no. 2020, pp.1-6.
https://search.emarefa.net/detail/BIM-1142243
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1142243