Research on Sentiment Classification Algorithms on Online Review

Joint Authors

Wang, Xiaoli
Yan, Ruixia
Xia, Zhijie
Xie, Yanxi
Song, Zukang

Source

Complexity

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

Philosophy

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