Analysis of Microblog Public Opinion Based on BERT Model

Author:

Gai Xiao-Tang1

Affiliation:

1. College of Computer Science of Sichuan University, China and Wu Yuzhang Honors College of Sichuan University, China

Publisher

ACM

Reference13 articles.

1. Microblog public opinion analysis system based on crawler and text processing[J];Liu Ziqian;Institute of Electronic Science and Technology of Beijing,2020

2. Yuanyuan Fang . Analysis of network public opinion based on text mining and sentiment analysis——Take the COVID-19 outbreak, for example[D] . Anhui University of Finance and Economics , 2021 . Yuanyuan Fang. Analysis of network public opinion based on text mining and sentiment analysis——Take the COVID-19 outbreak, for example[D]. Anhui University of Finance and Economics,2021.

3. Guo K, Shi L, Ye W , A survey of internet public opinion mining[C]//2014 IEEE international conference on progress in informatics and computing . IEEE , 2014 : 173-179. Guo K, Shi L, Ye W, A survey of internet public opinion mining[C]//2014 IEEE international conference on progress in informatics and computing. IEEE, 2014: 173-179.

4. Song C Guo C Hunt K Zhuang J. An Analysis of Public Opinions Regarding Take-Away Food Safety: A 2015–2018 Case Study on Micronblog. Foods. 2020; 9(4):511. https://doi.org/10.3390/foods9040511 Song C Guo C Hunt K Zhuang J. An Analysis of Public Opinions Regarding Take-Away Food Safety: A 2015–2018 Case Study on Micronblog. Foods. 2020; 9(4):511. https://doi.org/10.3390/foods9040511

5. Gongyong Cai , Qiang Cai , Kaiqi Ren . Cross-domain textual emotion analysis based on the domain adversarial network and BERT[J] . Journal of Shandong University (Engineering Edition) , 2020 ,50(1):1-7,20. DOI:10.6040/j.issn.1672-3961.0.2019.293. 10.6040/j.issn.1672-3961.0.2019.293 Gongyong Cai, Qiang Cai, Kaiqi Ren. Cross-domain textual emotion analysis based on the domain adversarial network and BERT[J]. Journal of Shandong University (Engineering Edition), 2020,50(1):1-7,20. DOI:10.6040/j.issn.1672-3961.0.2019.293.

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