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International Journal of Advanced Computer Science and Applications(IJACSA), Volume 14 Issue 12, 2023.
Abstract: The advancement of information technology has made the internet and social media an indispensable part of modern life, but with it comes a flood of false information and rumors. The aim of this study is to develop a technology that can automatically identify campus network public opinion information, in order to protect student groups from the intrusion of erroneous information, maintain their mental health, and promote a clear campus public opinion environment. This study used the Scrapy framework to write web scraping scripts to collect campus public opinion data, and carried out cleaning and preprocessing. Then, a transformer based generative adversarial network (T-GAN) model was designed, combined with a multi-scale convolutional neural network (MCNN) structure, for public opinion analysis on campus networks. The results show that the accuracy of the dataset processed by the T-GAN model has been improved on LGBT, KNN, SVM, and RoBERTa, proving that the campus network public opinion analysis model based on the T-GAN model helps to automatically identify campus network public opinion, protect students' physical and mental health, and promote the healthy development of the campus network environment.
Jianan Zhang, “The Construction of Campus Network Public Opinion Analysis Model Based on T-GAN Model” International Journal of Advanced Computer Science and Applications(IJACSA), 14(12), 2023. http://dx.doi.org/10.14569/IJACSA.2023.0141247
@article{Zhang2023,
title = {The Construction of Campus Network Public Opinion Analysis Model Based on T-GAN Model},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2023.0141247},
url = {http://dx.doi.org/10.14569/IJACSA.2023.0141247},
year = {2023},
publisher = {The Science and Information Organization},
volume = {14},
number = {12},
author = {Jianan Zhang}
}
Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.