AI Powered Anti-Cyber Bullying System using Machine Learning Algorithm of Multinomial Naive Bayes and Optimized Linear Support Vector Machine

被引：0

作者：

Ige, Tosin ^{[1
]}

Adewale, Sikiru ^{[2
]}

机构：

[1] Univ Texas El Paso, Dept Comp Sci, El Paso, TX 79968 USA

[2] Virginia Technol Univ, Dept Comp Sci, Blacksburg, VA USA

来源：

INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS | 2022年 / 13卷 / 05期

关键词：

Cyberbullying; anti cyberbullying; machine learning; NLP; social media; multinomial Naive Bayes; support vector machine;

D O I：

暂无

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

"Unless and until our society recognizes cyber bullying for what it is, the suffering of thousands of silent victims will continue." similar to Anna Maria Chavez. There had been series of research on cyber bullying which are unable to provide reliable solution to cyber bullying. In this research work, we were able to provide a permanent solution to this by developing a model capable of detecting and intercepting bullying incoming and outgoing messages with 92% accuracy. We also developed a chatbot automation messaging system to test our model leading to the development of Artificial Intelligence powered anti-cyber bullying system using machine learning algorithm of Multinomial Naive Bayes (MNB) and optimized linear Support Vector Machine (SVM). Our model is able to detect and intercept bullying outgoing and incoming bullying messages and take immediate action.

引用

页码：5 / 9

页数：5

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