Optimizing topic classification and sentiment analysis in Chinese car comments using CorEx algorithm based on BERT model

Chenanran Kong; Yanhao Chen; Yanting Liu

doi:10.1117/12.2681634

1 June 2023 Optimizing topic classification and sentiment analysis in Chinese car comments using CorEx algorithm based on BERT model

Chenanran Kong, Yanhao Chen, Yanting Liu

Author Affiliations +

Proceedings Volume 12718, International Conference on Cyber Security, Artificial Intelligence, and Digital Economy (CSAIDE 2023); 127182G (2023) https://doi.org/10.1117/12.2681634
Event: International Conference on Cyber Security, Artificial Intelligence, and Digital Economy (CSAIDE 2023), 2023, Nanjing, China

Abstract

Users' comments on cars are the focus of automobile companies, which can be used to analyze people's concerns and satisfaction with cars. Such a task is of great commercial value. There are more studies on end-to-end models for topic classification, but the method of manually extracting obvious features and transferring them to the model does not take much time and can improve the accuracy and convergence speed of the model. This study is based on a labeled car comments dataset. First, distinctive feature words are selected as anchor words, and the inclusion of anchor words will anchor this comment to the corresponding topic, making the topic classification and sentiment analysis more accurate. In addition, it is feasible to use a single Bert model to connect the token [CLS] to two linear layers respectively for topic classification and sentiment analysis. It shows that the BERT model with CorEx can improve the classification accuracy and convergence speed significantly, and has a good value in car review classification.

Citation Download Citation

Chenanran Kong, Yanhao Chen, and Yanting Liu "Optimizing topic classification and sentiment analysis in Chinese car comments using CorEx algorithm based on BERT model", Proc. SPIE 12718, International Conference on Cyber Security, Artificial Intelligence, and Digital Economy (CSAIDE 2023), 127182G (1 June 2023); https://doi.org/10.1117/12.2681634

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members: $17.00

Non-members: $21.00 ADD TO CART

PROCEEDINGS
5 PAGES

DOWNLOAD PAPER SAVE TO MY LIBRARY

GET CITATION

RIGHTS & PERMISSIONS

Get copyright permission Get copyright permission on Copyright Marketplace

KEYWORDS

Data modeling

Mathematical optimization

Performance modeling

Statistical modeling

Matrices

Deep learning

Machine learning

Show All Keywords

Keywords/Phrases

Search In:

Publication Years