| Autor: |
Reddy, K. Babu, Ramkumar, G. |
| Předmět: |
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| Zdroj: |
AIP Conference Proceedings; 2024, Vol. 2871 Issue 1, p1-8, 8p |
| Abstrakt: |
This study looks at how well a recurrent Neural Network and a logistic regression classifier can detect cyberbullying. Methods and Equipment Used in the Study: This approach makes use of two datasets. To find out how effective new cyberbullying deductions are, twenty instances were divided into two groups: one using logistic regression and the other using recurrent neural networks. This sample was calculated using G power and an 80% pretest power. Data pertaining to cyberbullying was used for training purposes using logistic regression and RNN. The two approaches, RNN and logistic regression, vary significantly in their accuracy levels; 94.58% vs. 94.55% (p>0.05). Lastly, the Recurrent Neural Network approach outperforms the logistic regression classifier. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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