Cross-domain Text Sentiment Classification Based on Auxiliary Classification Networks

Authors

Na Ma, 1.School of Business Administration, Liaoning Technical University, Huludao 125105, China;Follow
Tingxin Wen, 1.School of Business Administration, Liaoning Technical University, Huludao 125105, China;
Xu Jia, 2.School of Electronics and Information Engineering, Liaoning University of Technology, Jinzhou 121001, China;
Xiaohui Li, 2.School of Electronics and Information Engineering, Liaoning University of Technology, Jinzhou 121001, China;

Abstract

Abstract: To align exactly the texts with same sentiment polarities of source and target domains, and to enlarge the feature difference of different sentiment texts as much as possible, a domain adaptation model with weighted adversarial networks is proposed. A new structured classification network consisting of a main classification network and an auxiliary classification network is proposed, in which the main classification network is used to perform supervised learning on the labeled texts of the source domain, and the auxiliary classification network is used to improve the distinguishability of the text features. A calculation method of multiple adversarial network weights is proposed to realize the exact alignment of same class samples of different domains. Experimental results show that, for Amazon dataset, the average recognition accuracy for the texts of target domains can reach 84.22%, which is 2.07% higher than the compared models. The optimized feature extractor and the feature classifier can be applied to the source and target domains simultaneously on the proposed model, and can provide reliable data for the simulation and modeling of text analysis in different fields.

Recommended Citation

Ma, Na; Wen, Tingxin; Jia, Xu; and Li, Xiaohui (2023) "Cross-domain Text Sentiment Classification Based on Auxiliary Classification Networks," Journal of System Simulation: Vol. 35: Iss. 4, Article 4.
DOI: 10.16182/j.issn1004731x.joss.21-1283
Available at: https://dc-china-simulation.researchcommons.org/journal/vol35/iss4/4

First Page

721

Revised Date

2022-02-26

DOI Link

https://doi.org/10.16182/j.issn1004731x.joss.21-1283

Last Page

733

CLC

TP391.4

Recommended Citation

Na Ma, Tingxin Wen, Xu Jia, Xiaohui Li. Cross-domain Text Sentiment Classification Based on Auxiliary Classification Networks[J]. Journal of System Simulation, 2023, 35(4): 721-733.

DOI

10.16182/j.issn1004731x.joss.21-1283