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Chinese online comments sentiment analysis based on weighted char-word mixture word representation

Zhang Xiaoyan
Bai Yu
College of Computer Science & Technology, Xi'an University of Science & Technology, Xi'an 710600, China

Abstract

The widespread use of social networking platforms has led to the emergence of emotionally rich online comment texts, analyzing the emotions expressed in comments is of great significance to companies, platforms, etc. In order to solve the current problem of weak feature extraction ability and ignoring the emotional information of short text in online comment short text sentiment analysis, this paper proposed a model based on text sentiment value weighted char-word mixture word representation-SVW-BERT. First, it based on the fusion of character and word level vectors represented text vectors for maximizing semantic representation. At the same time, considering the influence of adverbs, negative words, exclamation sentences and interrogative sentences on the sentiment of the text, it used the weight to calculate the sentiment value of the text, and constructed sentiment analysis model of Chinese short text based on text sentiment value weighted char-word mixture word representation. Through the network platform online reviews data set, it validated the feasibility and the advantages of the model. The experimental results show that the char-word mixture word representation is stronger in semantic extraction, and the sentiment value weighted sentence vector considers the sentiment information contained in the text itself, which achieves the effect of improving the ability of sentiment classification.

Foundation Support

国家自然科学青年基金资助项目(61902311)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2021.06.0253
Publish at: Application Research of Computers Printed Article, Vol. 39, 2022 No. 1
Section: Algorithm Research & Explore
Pages: 31-36
Serial Number: 1001-3695(2022)01-005-0031-06

Publish History

[2021-11-14] Accepted Paper
[2022-01-05] Printed Article

Cite This Article

张小艳, 白瑜. 基于加权融合字词向量的中文在线评论情感分析 [J]. 计算机应用研究, 2022, 39 (1): 31-36. (Zhang Xiaoyan, Bai Yu. Chinese online comments sentiment analysis based on weighted char-word mixture word representation [J]. Application Research of Computers, 2022, 39 (1): 31-36. )

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  • Application Research of Computers Monthly Journal
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Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

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