Chinese Microblog Sentiment Detection Based on CNN-BiGRU and Multihead Attention Mechanism

Joint Authors

Qiu, Hong
Fan, Chongdi
Yao, Jie
Ye, Xiaohan

Source

Scientific Programming

Issue

Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-13, 13 p.

Publisher

Hindawi Publishing Corporation

Publication Date

2020-10-15

Country of Publication

Egypt

No. of Pages

13

Main Subjects

Mathematics

Abstract EN

With the rapid development of the Internet, Weibo has gradually become one of the commonly used social tools in society at present.

We can express our opinions on Weibo anytime and anywhere.

Weibo is widely used and people can express themselves freely on it; thus, the amount of comments on Weibo has become extremely large.

In order to count up the attitudes of users towards a certain event, Weibo managers often need to evaluate the position of a certain microblog in an appropriate way.

In traditional position detection tasks, researchers mainly mine text semantic features through constructing feature engineering and sentiment dictionary, but it takes a large amount of manpower in feature selection and design.

However, it is an effective method to analyze the sentiment state of microblog comments.

Deep learning is developing in an increasingly mature direction, and the utilization of deep learning methods for sentiment detection has become increasingly popular.

The application of convolutional neural networks (CNN), bidirectional GRU (BiGRU), and multihead attention mechanism- (multihead attention-) combined method CNN-BiGRU-MAttention (CBMA) to conduct Chinese microblog sentiment detection was proposed in this paper.

Firstly, CNN were applied to extract local features of text vectors.

Afterward, BiGRU networks were applied to extract the global features of the text to solve the problem that the single CNN cannot obtain global semantic information and the disappearance of the traditional recurrent neural network (RNN) gradient.

At last, it was concluded that the CBMA algorithm is more accurate for Chinese microblog sentiment detection through a variety of algorithm experiments.

American Psychological Association (APA)

Qiu, Hong& Fan, Chongdi& Yao, Jie& Ye, Xiaohan. 2020. Chinese Microblog Sentiment Detection Based on CNN-BiGRU and Multihead Attention Mechanism. Scientific Programming،Vol. 2020, no. 2020, pp.1-13.
https://search.emarefa.net/detail/BIM-1209266

Modern Language Association (MLA)

Qiu, Hong…[et al.]. Chinese Microblog Sentiment Detection Based on CNN-BiGRU and Multihead Attention Mechanism. Scientific Programming No. 2020 (2020), pp.1-13.
https://search.emarefa.net/detail/BIM-1209266

American Medical Association (AMA)

Qiu, Hong& Fan, Chongdi& Yao, Jie& Ye, Xiaohan. Chinese Microblog Sentiment Detection Based on CNN-BiGRU and Multihead Attention Mechanism. Scientific Programming. 2020. Vol. 2020, no. 2020, pp.1-13.
https://search.emarefa.net/detail/BIM-1209266

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references

Record ID

BIM-1209266